Acceptability Of mHealth Research Articles

The feasibility of M-health for people with chronic low back pain in Shanghai, China: A qualitative study

Background: Mobile health (M-health) has emerged as a promising solution for enhancing the management of low back pain. However, the feasibility of M-health among the Chinese population and its influencing factors remain unclear. Objective: This study aimed to assess the acceptance of M-health among people with chronic low back pain (CLBP) and physiotherapists in Shanghai, China, and to explore the influencing factors of its utility in the treatment of CLBP. Methods: Semi-structured interviews and focus groups were conducted with 25 participants with CLBP and 20 physiotherapists, utilising a combination of group discussion and individual interview. Thematic analysis, supported by NVivo software, was employed to identify and examine the themes regarding the facilitators and barriers to the utility of M-health in Shanghai, China. Results: The focus group discussions revealed a broad spectrum of factors that drive or hinder participants’ acceptance of M-health. Three main themes related to the feasibility of M-health were identified from the interviews: (1) Reasons for embracing M-health; (2) Reasons for resisting M-health; (3) Recommendations to enhance the feasibility of M-health. In general, participants exhibited enthusiasm towards the prospect of offering M-health as a viable treatment. Conclusions: The findings of this study indicate that the feasibility of M-health depends on many factors in Shanghai, China. Efforts to promote the establishment of M-health policy or laws, rational integration of M-health and face-to-face model and improvement of the functions of M-health applications may increase its feasibility in Shanghai, China.

Acceptance of Mhealth by Patients with Cardiovascular Diseases: the Structural Model of Health Applications Use

Acceptance of Mhealth by Patients with Cardiovascular Diseases: the Structural Model of Health Applications Use

Determinants of the intention to use mHealth in the future: Evidence from an intervention study of patients with chronic diseases in Slovenia

BackgroundMobile health (mHealth) implementation is crucial for developing sustainable healthcare systems, but it faces the challenge of user acceptance. Extending traditional acceptance models allows for the cognitive, emotional and social aspects of engaging with mHealth to be captured, creating a more comprehensive understanding of users’ intentions to use it in the future. User-centred intervention studies based on users’ real experiences with mHealth are essential for accurate assessments and for improving upon studies that rely merely on anticipated mHealth use. MethodsAn intervention study was conducted with 103 patients with at least one chronic condition (type 2 diabetes and/or arterial hypertension) who had used an mHealth service for three months. They were recruited through purposive sampling at a community health centre in Slovenia. Path analysis was applied to the survey data collected after a three-month testing period to validate an explanatory model with eight hypotheses. ResultsThe intensity of mHealth use affected usability, which in turn affected acceptability, the psychosocial impacts of engagement with mHealth and intention for future use. The results showed that the intensity of mHealth use did not affect mHealth acceptability. Likewise, acceptability did not affect the psychosocial impacts of engagement with mHealth or the intention for its future use. Notably, perceptions of the psychosocial impacts of mHealth had no significant effect on the intention for future use. ConclusionUsability and intensity of use play a central role in the post-intervention usage of mHealth, offering valuable insights for policymakers and healthcare providers involved in the delivery of mHealth-based treatment to patients with chronic diseases.

Social Acceptance of Mobile Health Technologies Among the Young Population in Nigeria

Mobile devices are widely used in modernizing healthcare delivery because of their unique features related to accessibility, virtual interaction, and connectivity. While developing countries, with limited resources, strive to achieve high healthcare standards, and mobile health (mHealth) solutions could transform healthcare delivery systems in these countries, their functionality is currently limited. This study investigates the potential systematic introduction of mHealth services and their social acceptability in developing countries, with a particular focus on Nigeria. This cross-sectional study was conducted with a sample of university students. Structural equation modeling was used to test the study hypotheses, and descriptive statistics were used to analyze the sociodemographic characteristics of the participants. Psychological and personal characteristics, environmental characteristics, and conditions of use associated with mHealth technology adoption were examined based on eight constructs (health consciousness, trust, social influence, perceived risk, performance expectancy, facilitating conditions, effort expectancy, and behavioral intention). The results indicate that trust and performance expectancy are significant predictors of mHealth acceptance in the surveyed population. The future acceptance of mHealth among young people in developing countries holds great significance for improving healthcare delivery, addressing the unique challenges faced by developing countries, and leveraging the preferences of young individuals, which could contribute to the advancement of mHealth solutions and enhance healthcare accessibility. The findings shed light on the acceptance of mHealth technologies among the young populations of developing countries, with implications for future efforts to improve healthcare delivery and address the healthcare challenges of these countries.

The role of mHealth intervention to improve maternal and child health: A provider-based qualitative study in Southern Ethiopia.

Maternal and child mortality remained higher in developing regions such as Southern Ethiopia due to poor maternal and child health. Technologies such as mobile applications in health may be an opportunity to reduce maternal and child mortality because they can improve access to information. Therefore, the main aim of this study was to explore the role of mHealth in improving maternal and child health in Southern Ethiopia. This study employed a qualitative study design to explore the role of mHealth in improving maternal and child health among health professionals in Southern Ethiopia from December 2022 to March 2023. We conducted nine in-depth interviews, six key informants' in-depth interviews, and four focused group discussions among health professionals. This is followed by thematic analyses to synthesize the collected evidence. The results are based on 226 quotations, 5 major themes, and 24 subthemes. The study participants discussed the possible acceptance of mHealth in terms of its fitness in the existing health system, its support to health professionals, and its importance in improving maternal and child health. The participants ascertained the importance of awareness creation before the implementation of mHealth among women, families, communities, and providers. They reported the importance of mHealth for mothers and health professionals and the effectiveness of mHealth services. The participants stated that the main challenges related to acceptance, awareness, negligence, readiness, and workload. However, they also suggested strategic solutions such as using family support, provider support, mothers' forums, and community forums. The evidence generated during this analysis is important information for program implementations and can inform policy-making. The planned intervention needs to introduce mHealth in Southern Ethiopia. Planners, decision-makers, and researchers can use it in mobile technology-related interventions. For challenges identified, we recommend solution-identified-based interventions and quality studies.

Use of mHealth in promoting maternal and child health in "BIMARU" states of India "A health system strengthening strategy": Systematic literature review.

Low-middle income countries like India bear a heavier burden of maternal, childcare, and child mortality rates when compared with high-income countries, which highlights the disparity in global health. Numerous societal, geopolitical, economic, and institutional issues have been linked to this inequality. mHealth has the potential to ameliorate these challenges by providing health services and health-related information with the assistance of frontline workers in the provision of prepartum, delivery, and postnatal care to improve maternal and child health outcomes in hard-to-reach areas in low- and middle-income countries (LMICs). However, there is limited evidence to support how mHealth can strengthen maternal and child health in India. The scoping review guideline in the Cochrane Handbook was used to retrieve studies from 4 international databases: CINAHL, Embase, Medline Ovid, and PubMed. This search strategy used combined keywords (MeSH terms) related to maternal and child healthcare, mHealth, and BIMARU in conjunction with database-controlled vocabulary. Out of 278 records, 8 publications were included in the review. The included articles used mHealth for data collection, eLearning, communication, patient monitoring, or tracking to deliver maternal and neonatal care. The results of these papers reflected a favourable effect of mHealth on the target population and found that it altered their attitudes and behaviours about healthcare. Higher job satisfaction and self-efficiency were reported by mHealth user care providers. Multiple barriers to the acceptance of mHealth exist, but the majority of the evidence points towards the feasibility of the intervention in a clinical setting. The mHealth has positive potential for improving maternal and child health outcomes in low-resource settings in India's BIMARU states by strengthening the healthcare system. The results of the study could be used in the tailoring of an effective mHealth intervention and implementation strategy in a similar context. However, there is a need for economic evaluation in the future to bridge the knowledge gap regarding the cost-effectiveness of mHealth interventions.

The feasibility of an educational and monitoring smartphone application for patients with advanced renal cell carcinoma undergoing combination immunotherapy.

413 Background: Renal Cell Carcinoma (RCC) is a global public health burden with over 400,000 new cases and over 175,000 deaths annually. Immune checkpoint inhibitors (ICI) in combination with vascular endothelial growth factor tyrosine kinase inhibitors (VEGF-TKI) has become an integral part of the management of patients with advanced RCC which requires adaptation of healthcare systems to provide information and optimize the management of drug-related adverse events. This study aims to improve the education on therapy-related symptoms and the quality of life of patients with RCC treated with these drugs. Methods: We created a smartphone application (mHealth) that combines educational data, patient-reported outcomes, and peer-to-peer interactions. We aim to assess the feasibility of expansion of this pilot study. We prospectively enrolled stage IV RCC patients (n=20) undergoing treatment with combination ICI and VEGF-TKI. Therapy-related symptom education, knowledge PRO questionnaires, and peer-to-peer support were provided at baseline and at different time points throughout this study duration (Table 1). Time-course data of PROs were visualized using line plots and then compared with paired t-tests. The study's primary endpoint was to assess acceptability and feasibility of mHealth, defined as acceptable if 50% of patients offered participation agree to be enrolled and feasible if 50% of enrolled patients complete the intervention with 70% of these completing at least 50% of survey instruments. Results: Eighty percent of patients were male, 80% were white, 75% had at least some college education, 70% were married, and the mean age of the cohort was 66 years.A total of 22 patients were approached for the study with an acceptance rate of 90%. Sixty percent of patients completed every questionnaire and knowledge assessment at every timepoint of the intervention and 75% of those completed at least 50% of instruments. PROs data showed no significant difference compared to baseline in global health status, functional scales, and symptom scales across the 24 weeks. We noticed an improvement in the patients' knowledge assessment on symptom management after completion of the mHealth knowledge component. Conclusions: Our pilot study was considered acceptable and feasible, showing preliminary evidence of improvement in patient knowledge with mHealth. Our future direction will be to assess, in a larger randomized study, the efficacy of mHealth in improving the quality of life of patients with advanced RCC treated with ICI and VEGF-TKI. Clinical trial information: NCT05579847 . [Table: see text]

Predicting m-health acceptance from the perspective of unified theory of acceptance and use of technology

Addressing the growing popularity of mobile health (m-Health) technology in the health industry, the current study examined consumers’ intention and behaviour related to the usage of digital applications based on the unified theory of acceptance and use of technology (UTAUT). In particular, this study quantitatively assessed the moderating role of perceived product value and mediating role of intention to use m-Health application among Indonesians. This study adopted a cross-sectional design and collected quantitative data from conveniently selected respondents through an online survey, which involved 2068 Telegram users in Indonesia. All data were subjected to the analysis of partial least square- structural equation modeling (PLS-SEM). The obtained results demonstrated the moderating effect of perceived product value on the relationship between intention to use m-Health application (m-health app) and actual usage of m-Health app and the mediating effects of intention to use m-Health app on the relationships of perceived critical mass, perceived usefulness, perceived convenience, perceived technology accuracy, and perceived privacy protection on actual usage of m-Health app. However, the intention to use m-Health app did not mediate the influence of health consciousness and health motivation on the actual usage of m-Health app. Overall, this study’s findings on the significance of intention to use m-Health app and perceived product value based on the UTAUT framework serve as insightful guideline to expand the usage of m-Health app among consumers.

Preferences, Acceptability and Usage of Mobile Health Applications Among Undergraduate Nursing Students: A Multisite, Cross-Sectional Survey.

Mobile health applications (mHealth) can bring revolutionary changes to health care by making it more accessible, cost-effective, and efficient. The successful adoption of mHealth is largely determined by its acceptance by providers and end users. The acceptance of mHealth among nursing students, who are the future nurses, needs to be understood. This study aimed to determine the preferences, acceptability, and usage of mHealth applications among undergraduate nursing students. A descriptive cross-sectional study was conducted in two selected universities in southern and northern India. A convenience sample of 567 undergraduate nursing students was recruited for the study. The data were collected using a structured questionnaire via Google Forms. mHealth applications were presently used by 32.9% of the students. The most common types of mHealth applications used were diet related (27.6%) and lifestyle related (23.4%). The majority of nursing students were willing to use mobile phones for consulting health professionals (78.8%) for prevention and management of health and disease. (83.1%), and for emergencies (73.3%). While more than half of the students were willing to recommend mHealth applications for patients, those students who were using two or more mHealth apps were more likely to recommend the same for the patients. The results of the study highlight about the usage of mobile health applications among the nursing students. The students consider mHealth applications to be useful for delivering health-related services to end users. The study underscores the need to sensitize students about the possible usage of mHealth in healthcare delivery.

Influencing Factors to mHealth Uptake With Indigenous Populations: Qualitative Systematic Review.

The advancements and abundance of mobile phones and portable health devices have created an opportunity to use mobile health (mHealth) for population health systems. There is increasing evidence for the feasibility and acceptance of mHealth with Indigenous populations. Providing a synthesis of qualitative findings of mHealth with Indigenous populations will gain insights into the strengths and challenges to mHealth use in Indigenous populations. This review aimed to identify and synthesize qualitative data pertaining to the experiences and perceptions of mHealth from the perspectives of end users (patients and service providers) living in the colonial settler democracies of Canada, Australia, New Zealand, the United States, the Pacific Islands, and the Sápmi region of northern Europe. In May 2021, systematic searches of peer-reviewed, scientific papers were conducted across the 5 databases of PubMed, CINAHL, Embase, PsycINFO, and Web of Science. Qualitative or mixed method studies were included where a mHealth intervention was the primary focus for responding to health challenges with Indigenous populations. Two authors independently screened papers for eligibility and assessed the risk of bias using a modified version of the Critical Appraisal Skills Programme. A meta-aggregative approach was used to analyze the findings of included studies. Seventeen papers met the eligibility criteria, 8 studies with patients, 7 studies with service providers, and 2 studies that included both patients and service providers. Studies were conducted in Australia (n=10), Canada (n=2), New Zealand (n=2), Papua New Guinea (n=1), the United States (n=1), and Samoa (n=1). Our interpretation of these qualitative findings shows commonalities between Indigenous patients' and service providers' perceptions of mHealth. We summarize our findings in six themes: (1) mHealth literacy, (2) mHealth as a facilitator for connection and support, (3) mHealth content needed to be culturally relevant, (4) mHealth security and confidentiality, (5) mHealth supporting rather than replacing service providers, and (6) workplace and organizational capacity. This research suggests that mHealth can meet the needs of both patients and service providers when the mHealth intervention is culturally relevant, accounts for digital and health literacy, incorporates interactive components, is supported by workplaces, fits into health provider workflows, and meets security and confidentiality standards. Future mHealth research with Indigenous populations should partner with key representatives (eg, patients, service providers, and executive leaders) in the mHealth design appropriate to the purpose, people, setting, and delivery.

Factors Predicting Older People's Acceptance of a Personalized Health Care Service App and the Effect of Chronic Disease: Cross-Sectional Questionnaire Study.

Mobile health (mHealth) services enable real-time measurement of information on individuals' biosignals and environmental risk factors; accordingly, research on health management using mHealth is being actively conducted. The study aims to identify the predictors of older people's intention to use mHealth in South Korea and verify whether chronic disease moderates the effect of the identified predictors on behavioral intentions. A cross-sectional questionnaire study was conducted among 500 participants aged 60 to 75 years. The research hypotheses were tested using structural equation modeling, and indirect effects were verified through bootstrapping. Bootstrapping was performed 10,000 times, and the significance of the indirect effects was confirmed through the bias-corrected percentile method. Of 477 participants, 278 (58.3%) had at least 1 chronic disease. Performance expectancy (β=.453; P=.003) and social influence (β=.693; P<.001) were significant predictors of behavioral intention. Bootstrapping results showed that facilitating conditions (β=.325; P=.006; 95% CI 0.115-0.759) were found to have a significant indirect effect on behavioral intention. Multigroup structural equation modeling testing the presence or absence of chronic disease revealed a significant difference in the path of device trust to performance expectancy (critical ratio=-2.165). Bootstrapping also confirmed that device trust (β=.122; P=.039; 95% CI 0.007-0.346) had a significant indirect effect on behavioral intention in people with chronic disease. This study, which explored the predictors of the intention to use mHealth through a web-based survey of older people, suggests similar results to those of other studies that applied the unified theory of acceptance and use of technology model to the acceptance of mHealth. Performance expectancy, social influence, and facilitating conditions were revealed as predictors of accepting mHealth. In addition, trust in a wearable device for measuring biosignals was investigated as an additional predictor in people with chronic disease. This suggests that different strategies are needed, depending on the characteristics of users.

717-P: Unmet Needs and Communication Preferences for mHealth Self-Management Solutions in People with Type 1 Diabetes and Insulin Resistance

Insulin resistance (IR) is prevalent within type 1 diabetes (T1D) and associated with increased morbidity and mortality. Mobile health (mHealth) applications are useful platforms for delivering health behaviour interventions, but technologies focusing on addressing IR in T1D are absent. The aim of this formative study was to identity salient unmet patient needs, communication preferences, and barriers for mHealth self-management solutions in people with T1D and IR. 70 adults with type 1 diabetes (male=57%; HbA1c 8.1±3.4%; 28±5years) completed an online survey evaluating skills gaps in self-management and priorities for diabetes mHealth apps. Survey responses were ranked using a 9-point scale and analysed using descriptive and inferential statistics. Qualitative write-in responses were subsequently coded and analysed using inductive thematic analysis. IR was assessed using estimated glucose disposal rate (eGDR). Among all respondents, 49% (n=34) identified glycemic control/variability as the principle unmet self-management need. Fewer than 5% (n=3) reported having no self-perceived skills gaps. 89% (n=62) identified paternalistic communication and weight stigmatization as barriers to mHealth use. Real-life/situational feedback for glucose control/variability was reported as the single largest facilitator of mHealth use (65%, n=46). Preferred communication strategies were empathy, concern, and compassion (81%, n=57), and informal, open, and direct (77%, n=54). Our results highlight that glucose control/variability is the principle unmet self-management need in T1D adults with IR. Several communication barriers negatively impact mHealth acceptability and efficacy in this group, particularly paternalistic and weight-stigmatizing language. mHealth solutions that target glycemic control/variability and are non-weight stigmatizing are urgently needed for people with T1D and IR. Disclosure A.R.Wilson: None. M.Farrar: None. M.D.Campbell: None.

Acceptability of an mHealth App for Monitoring Perinatal and Postpartum Mental Health: Qualitative Study With Women and Providers.

Up to 15% of pregnant and postpartum women commonly experience undiagnosed and untreated mental health conditions, such as depression and anxiety, which may result in serious health complications. Mobile health (mHealth) apps related to mental health have been previously used for early diagnosis and intervention but not among pregnant and postpartum women. This study aims to assess the acceptability of using mHealth to monitor and assess perinatal and postpartum depression and anxiety. Focus group discussions with pregnant and postpartum women (n=20) and individual interviews with health care providers (n=8) were conducted to inform the acceptability of mHealth and determine its utility for assessing perinatal and postpartum mood symptoms. Participants were recruited via purposive sampling from obstetric clinics and the surrounding community. A semistructured interview guide was developed by an epidemiologist with qualitative research training in consultation with an obstetrician. The first author conducted all focus group discussions and provider interviews either in person or via Zoom (Zoom Video Communications, Inc) depending on the COVID-19 protocol that was in place during the study period. All interviews were audio recorded with consent; transcribed; and uploaded for coding to ATLAS.ti 8 (ATLAS.ti Scientific Software Development Gmb H), a qualitative data analysis and retrieval software. Data were analyzed using the deductive content analysis method using a set of a priori codes developed based on the interview guide. Methodological rigor and quality were ensured by adopting a systematic approach during the implementation, data collection, data analysis, and reporting of the data. Almost all women and providers had downloaded and used at least 1 health app. The respondents suggested offering short questions in layperson language that could be understood by women of all educational levels and offering no more than 2 to 3 assessments per day at preferred timings decided by the women themselves. They also suggested that the women themselves receive the alerts first, with other options being family members, spouses, or friends if the women themselves did not respond within 24 to 72 hours. Customization and snooze features were strongly endorsed by women and providers to improve acceptability and utility. Women mentioned competing demands on their time during the postpartum period, fatigue, privacy, and the security of mental health data as concerns. Health care professionals highlighted the long-term sustainability of app-based mood assessment and monitoring as an important challenge. The findings from this study show that mHealth would be acceptable to pregnant and postpartum women for monitoring mood symptoms. This could inform the development of clinically meaningful and inexpensive tools for facilitating the continuous monitoring of, the early diagnosis of, and an early intervention for mood disorders in this vulnerable population.

Modeling Consumer Acceptance and Usage Behaviors of m-Health: An Integrated Model of Self-Determination Theory, Task-Technology Fit, and the Technology Acceptance Model.

Although mobile health (m-health) has great potential to reduce the cost of medical care and improve its quality and efficiency, it is not widely accepted by consumers. In addition, there is still a lack of comprehensive insight into m-health acceptance, especially among consumers with different demographic characteristics. This study aimed to explore the factors affecting consumers' acceptance and usage behaviors of m-health and to examine whether their roles differ by demographic characteristics. A comprehensive m-health acceptance model was proposed by integrating factors from the Self-Determination Theory, Task-Technology Fit, and Technology Acceptance Model. Survey data were collected from 623 Chinese adults with at least 6 months of m-health usage experience and analyzed using structural equation modeling techniques. Multi-group analyses were performed to assess whether the model relationships were different across gender, age, and usage experience. The results indicated that relatedness and competence were significant motivational antecedents of perceived ease of use. Task-technology fit and the perceived ease of use significantly affected the perceived usefulness. The perceived ease of use and perceived usefulness were significant determinants of consumer usage behaviors of m-health and together explained 81% of its variance. Moreover, the relationships among autonomy, perceived usefulness, and usage behaviors of m-health were moderated by gender. Consumer usage behaviors of m-health were affected by factors such as self-motivation (i.e., relatedness and competence), technology perceptions (i.e., perceived ease of use and perceived usefulness), and task-technology fit. These findings provide a theoretical underpinning for future research on m-health acceptance and provide empirical evidence for practitioners to promote the better design and use of m-health for healthcare activities.

Behavioral Predictors of Intention to Use a Text Messaging Reminder System Among People Living With HIV in Rural Uganda: Survey Study.

The expansion of cellular phones in sub-Saharan Africa spurred the development of SMS text message-based mobile health (mHealth) technology. Numerous SMS text message-based interventions have attempted to increase retention in care for people living with HIV in sub-Saharan Africa. Many of these interventions have failed to scale. Understanding theory-grounded factors leading to mHealth acceptability is needed to create scalable, contextually appropriate, and user-focused interventions to improve longitudinal HIV care for people living with HIV in sub-Saharan Africa. In this study, we aimed to understand the relationship between constructs from the Unified Theory of Acceptance and Use of Technology (UTAUT), constructs identified in previous qualitative research, and behavioral intention to use a novel SMS text message-based mHealth intervention designed to improve care retention among people living with HIV initiating treatment in rural Uganda. We conducted a survey of people living with HIV who were newly initiating HIV care in Mbarara, Uganda, and had agreed to use a novel SMS text message-based system that notified them of abnormal laboratory results and reminded them to return to the clinic. Survey items assessed behavioral intention to use the SMS text messaging system; constructs from UTAUT; and demographics, literacy, SMS text messaging experience, HIV status disclosure, and social support. We used factor analysis and logistic regression to estimate the relationships between UTAUT constructs and the behavioral intention to use the SMS text messaging system. A total of 249 participants completed the surveys, of whom 115 (46.2%) expressed high behavioral intention to use the SMS text messaging intervention. In a multivariable analysis, we found that performance expectancy (adjusted odds ratio [aOR] of the scaled factor score 5.69, 95% CI 2.64-12.25; P<.001), effort expectancy (aOR of the scaled factor score 4.87, 95% CI 1.75-13.51; P=.002), and social influence (measured as a 1-unit Likert score increase in the perception that clinical staff have been helpful in the use of the SMS text messaging program; aOR 3.03, 95% CI 1.21-7.54; P=.02) were significantly associated with high behavioral intention to use the SMS text messaging program. SMS text messaging experience (aOR/1-unit increase 1.48, 95% CI 1.11-1.96; P=.008) and age (aOR/1-year increase 1.07, 95% CI 1.03-1.13; P=.003) were also significantly associated with increased odds of high intention to use the system. Performance expectancy, effort expectancy, and social influence, as well as age and SMS experience, were drivers of high behavioral intention to use an SMS text messaging reminder system among people living with HIV initiating treatment in rural Uganda. These findings highlight salient factors associated with SMS intervention acceptability in this population and indicate attributes that are likely to be key to the successful development and scaling of novel mHealth interventions.

Predicting mHealth Acceptance Using the UTAUT2 Technology Acceptance Model: A Mixed-Methods Approach.

Mobile health (mHealth) apps are increasingly used in healthcare to support people with chronic diseases such as diabetes. mHealth acceptance is crucial for using them. Due to acceptance problems, however, mHealth apps are not used by all chronic disease patients. To predict user acceptance, technology acceptance models such as UTAUT2 are used. However, UTAUT2 was not explicitly developed for the mHealth context. This study investigates if additional health-related constructs could increase the predictive power of the UTAUT2 model. A mixed-methods design, comprising an initial qualitative methods triangulation study that consisted of a literature search, expert interviews, and patient interviews, and a subsequent quantitative cross-sectional survey with 413 patients was used. The mixed-methods study revealed and validated two new constructs relevant for predicting mHealth acceptance not represented in the UTAUT2 model: "perceived disease threat" and "trust". The UTAUT2 model was successfully extended by two new constructs relevant to the mHealth context.

Technology readiness and the older citizen’s acceptance of m-health services in India

PurposeThe purpose of this study was to create a theoretical model by combining the technology acceptance model (TAM) with the theory of technology readiness (TR) and then empirically test it to identify the key factors influencing older citizens’ intention to adopt and use mobile health (m-health), which has emerged as a tool to facilitate health-care rights for all.Design/methodology/approachThe convenience sampling method was used to collect data from 465 respondents aged 60 and up from the Delhi-National capital region of India using a questionnaire survey method. The data collected for this study were analyzed using partial least squares structural equation modeling using SmartPLS 3.0.FindingsThe study’s findings indicate that all TR components influence perceived usefulness (PU) and ease of use. The exception is discomfort, which does not affect perceived ease of use (PEOU). Furthermore, PU and PEOU influenced the older citizen’s attitude toward m-health, and attitude influenced their intention to use m-health applications.Originality/valueTo the best of the authors’ knowledge, this is the first study to apply the TAM in combination with TR index to examine the acceptability of m-health consulting by the older citizen in an emerging economy like India.

The role of trust and habit in the adoption of mHealth by older adults in Hong Kong: a healthcare technology service acceptance (HTSA) model

BackgroundEvidence from the literature suggests that mobile health (mHealth) services can potentially improve healthcare outcomes among older adults. Hence, the government of Hong Kong has recently taken several community and information technology (IT) services initiatives to train older adults on how to enhance their abilities and interest in using mHealth technology. Although mHealth services have been widely implemented globally, their adoption and use by older adults are very low, including those in Hong Kong. This study aims to understand key factors influencing mHealth use intention among the older Chinese population in Hong Kong.MethodsWe extended the Unified Theory of Acceptance and Use of Technology (UTAUT2) as the basis of our conceptual framework. We applied Partial Least Squares path modeling method to conduct the Structural Equation Model (SEM) technique that allows measuring the theoretical validity of any conceptual framework. Convenience and snowball sampling methods were used to recruit participants aged 65 or above. In total, 201 valid responses were used for testing the theoretical validity of the proposed conceptual framework.ResultsThe primary finding shows that the widely used UTAUT2 model falls short in explaining mHealth service acceptance behavior in the Chinese older population in Hong Kong. We further propose a simplified model, the Healthcare Technology Service Acceptance (HTSA) model, to understand the formation of mHealth service acceptance behavior. The findings show that trust is an important component of technology service acceptance intention behavior that was missing in the UTAUT2 model. The results also show that several antecedent factors (i.e., social influence, government policy, and service quality) are critical in forming technology trust beliefs.ConclusionsThe study shows that the HTSA model can better explain mHealth acceptance behavior than the UTAUT2 model. This study advances knowledge in the mHealth technology adoption domain by proposing a simplified new version of the UTAUT2 model for understanding healthcare technology service acceptance and use intention among older adults. The findings of the study provide valuable information to the Hong Kong government and healthcare organizations for wider adoption of mHealth services, especially in older adults.

Patient Acceptance of Prescribed and Fully Reimbursed mHealth Apps in Germany: An UTAUT2-based Online Survey Study

The study aims to (1) investigate current levels of patient acceptance of mHealth in Germany; (2) determine the influencing factors of patients' intention to use, and (3) test the influence of prescription and reimbursement status on patient acceptance. Online survey with 1349 participants, of which 1051 were complete and included for statistical analysis, from a broad cross-section of the German population, addressing both users of mobile health (mHealth) applications and people without prior experience. SEM modeling based on a combination of two theoretical frameworks: the extended Unified Theory of Acceptance and Use of Technology and Health Protective Behavior Theories were used to assess acceptance. Users of mHealth in Germany are mostly patients between the ages of 30 – 50 with mental health or endocrine conditions. General willingness to use mHealth apps / DiGAs (mHealth apps fully reimbursed by social health insurance) is high at 76%, especially if they are governmentally certified, however only 27% of respondents were willing to pay out of pocket. With the exception of a spike in performance expectancy and data security, DiGAs lack a clear differentiation from mHealth apps. Perceived self-efficacy and performance expectancy are significant predictors of willingness to use digital health interventions; with age, attitude, and e-literacy being key demographic predictors. A key takeaway for regulators, providers of mHealth apps/ DiGAs, and other stakeholders involved in mHealth adoption is the importance of addressing negative beliefs early on, targeted communication around effortless usage of mHealth services across age groups and demographics, and focus on highlighting expected benefits of mHealth app/ DiGA usage.

Understanding Factors Affecting the Use of Mobile Health Innovation, Attitude and Synthesis

Advancements in information and communication technologies have positively affected various sectors, and healthcare is no exception. Healthcare industry has been affected by smartphones that caused the use of mobile phones for providing healthcare services, which is known as Mobile health (mHealth). Regardless the benefits of mHealth, the success of this technology ultimately depends on public acceptance. Therefore, the objective of this research is to evaluate the acceptance of mHealth applications. An online survey was employed to collect data related to the variables in the conceptual model. This study utilizes the multivariate PLS-SEM method to evaluate the suggested model. The results indicate that four factors are important for the acceptance of mHealth: perceived usefulness, subjective norms, facilitating conditions and attitude toward behavior. In conclusion, the four factors are important, and decision makers should pay more attention to them to improve the public acceptance of mHealth.