Determinants of readiness to adopt mHealth in a rural community of Bangladesh

E-classroom as a Blended Learning Tool: A Structural Equation Modelling Analysis Using Modified Technology Acceptance Model

BACKGROUND

E-classrooms help teachers save time, keep classes organized, and improve communication with students. This study aims to assess Google Classroom's usefulness in enhancing medical students' knowledge and acceptance of new technology for in-depth learning.

MATERIAL AND METHOD

This educational interventional study was carried out on 100 students in the 3rd year of the M.B.B.S., Part 1. After a briefing about Google Classroom and educational topics, enrolled students and faculty were allowed to discuss the topic for two months. Following this, the descriptive approach was utilized to describe the respondents' technology acceptance through the administration of the technology acceptance model (TAM) survey questionnaire.

RESULTS

Students were actively involved in discussion, with a 67% response rate. Nearly 85% of students agreed that Google Classroom is a satisfactory way for in-depth knowledge acquisition. On factor analysis, it was observed that the goodness of fit was 0.985, suggesting that the model is acceptable. It was also found that perceived usefulness (PU) had a significant positive effect on motivation towards self-directed learning (SDL), and perceived ease of use (PEOU) had a positive effect on both behavioural intention and actual use.

CONCLUSION

Google Classroom is a valuable tool for learning that can enhance active self-learning and increase behavioural intention and actual use. It should be incorporated into day-to-day teaching activities to overcome time constraints.

Intention to use a mobile phone to receive mental health support and its predicting factors among women attending antenatal care at public health facilities in Ambo town, West Shoa zone, Ethiopia 2022

BACKGROUND

Mental health problems are the most common morbidities of women during the prenatal period. In LMICs mobile phones have been identified as a good vehicle for monitoring individuals with a high risk of mental health conditions. However, evidence is scarce and the purpose of this study was to assess the intention to use a mobile phone to receive mental health support and its predicting factors among women attending antenatal care at public health facilities in Ambo town, Ethiopia 2022.

METHODS AND MATERIALS

An institutional-based cross-sectional study design was conducted from May 20th to June 20th, 2022. A total of 715 prenatal women were included and a systematic random sampling technique was employed. An interviewer-administered structured questionnaire was used. Collected data was exported to SPSS version 25 for the descriptive part, and AMOS 26 structural equation modeling was also used to describe and assess the degree and significance of relationships between variables.

RESULTS

A total of 699 (97.8% response rate) responded to complete all the questionnaires. About 530 (77.3%) 95% CI (74%-80.3%) of women intended to use a mobile phone to receive mental health support. The perceived usefulness has a positive effect on attitude (β = 0.391, p < 0.001) and intention to use (β = 0.253, p < 0.001). The perceived ease of use influences perceived usefulness (β = 0.253, p < 0.001) and attitude β = 0.579, p < 0.001). The intention to use is positively affected by attitude (β = 0.662, p < 0.001).Trust has a positive effect on perceived usefulness (β = 0.580, p < 0.001) and intention to use (β = 0.113, p = 0.005). Subjective norm has a direct positive effect on perceived usefulness (β = 0.248, p < 0.001). Attitude serves as a partial mediator between perceived usefulness and intention to use and a complete mediating role between perceived ease of use and intention to use.

CONCLUSION

The level of intention to use a mobile phone among prenatal women is relatively high and attitude, perceived usefulness, and trust had direct positive effects on intention to use a mobile phone. Therefore, hospitals and healthcare providers should take proactive measures to implement the strategies and policies for providing mobile phone-based mental health support to prenatal women in remote areas.

Use of Telemedicine Technology among General Practitioners during COVID-19: A Modified Technology Acceptance Model Study in Poland

During the COVID-19 pandemic, telehealth became a popular solution for the remote provision of primary care by General Practitioners (GPs) in Poland. This study aimed to assess the GPs' acceptance of telehealth during the COVID-19 pandemic in Poland and to explain the factors that drive GPs' need to implement a telehealth system in primary care using the modified Technology Acceptance Model (TAM). In Poland, 361 GPs from a representative sample of 361 clinics drawn from 21,500 outpatient institutions in Poland participated in the empirical study. Structural equation modelling (SEM) was used to evaluate the causal relationships that were formulated in the proposed model. Research has shown that Polish GPs reported a positive perception and high acceptance of the telehealth system during the COVID-19 pandemic. Overall, the results show that the social factors (image, decision autonomy, perception of patient interaction) significantly positively influence the technological factors (perceived ease of use and perceived usefulness) that influence the need to implement a telehealth system. The proposed socio-technological model can serve as a theoretical basis for future research and offer empirical predictions for practitioners and researchers in health departments, governments, and primary care settings.

Strengthening urban primary healthcare service delivery using electronic health technologies: A qualitative study in urban Nepal

Background

Nepal is a South Asian country with a high burden of non-communicable diseases. Electronic health technologies are a promising strategy to mitigate the rising burden of non-communicable diseases by strengthening primary healthcare center service delivery. However, electronic health implementation in Nepal is limited. Furthermore, electronic health use at the primary healthcare center level is chronically understudied. This qualitative study seeks to understand the perceived awareness, benefits, and determinants of electronic health uptake in Nepal, focusing on primary healthcare center-level non-communicable disease management.

Methods

We conducted in-depth interviews with 27 participants including policymakers, health experts, facility administrators, providers, and non-communicable diseases patients in 2019. We selected six urban primary healthcare center facilities via cluster convenience sampling for recruiting facility administrators, providers, and patients, and used convenience sampling to recruit policymakers and experts. We conducted thematic data analysis inductively and deductively using the electronic health readiness assessment framework to understand perceived barriers and facilitators of electronic health implementation.

Results

While there was general awareness and acceptance of electronic health, multiple barriers impede readiness for implementation. These include policy making gaps, language barriers, low user technical literacy, concerns of overreliance on technology, and inadequate training for administrators and providers. Stakeholder suggestions include creating electronic health interfaces that meet the needs of end users (providers and patients), providing training to enable end users to effectively use electronic health technologies, and strong policy support at the national level.

Conclusion

We identify several determinants for effectively promoting the use of electronic health for non-communicable diseases service delivery at the primary healthcare center level in Nepal.

Mobile health applications: awareness, attitudes, and practices among medical students in Malaysia

BACKGROUND

The popularity of mobile health (mHealth) applications (or apps) in the field of health and medical education is rapidly increasing, especially since the COVID-19 pandemic. We aimed to assess awareness, attitudes, practices, and factors associated with the mHealth app usage among medical students.

METHODS

We conducted a cross-sectional study involving medical students at a government university in Sarawak, Malaysia, from February to April 2021. Validated questionnaires were administered to all consenting students. These questionnaires included questions on basic demographic information as well as awareness, attitude toward, and practices with mHealth apps concerned with medical education, health and fitness, and COVID-19 management.

RESULTS

Respondents had favorable attitudes toward mHealth apps (medical education [61.8%], health and fitness [76.3%], and COVID-19 management [82.7%]). Respondents' mean attitude scores were four out of five for all three app categories. However, respondents used COVID-19 management apps more frequently (73.5%) than those for medical education (35.7%) and fitness (39.0%). Usage of all three app categories was significantly associated with the respondent's awareness and attitude. Respondents in the top 20% in term of household income and study duration were more likely to use medical education apps. The number of respondents who used COVID-19 apps was higher in the top 20% household income group than in the other income groups. The most common barrier to the use of apps was uncertainty regarding the most suitable apps to choose.

CONCLUSION

Our study highlighted a discrepancy between awareness of mHealth apps and positive attitudes toward them and their use. Recognition of barriers to using mHealth apps by relevant authorities may be necessary to increase the usage of these apps.

Intrinsic antecedents to mHealth adoption intention - A SEM-ANN approach: Intrinsic antecedents to mHealth adoption intention

Healthcare is not left behind in the technological era, where almost every industry uses technological advances to serve customers' needs and wants. Increasingly, patients and doctors are using modern technological infrastructure to deliver care services. This study focuses on the intrinsic factors that lead to provider adoption of mHealth. The study uses PLS-SEM and neural networks to build on UTAUT theory. Study collects data from 316 care providers practicing in government and private health canters, hospitals and clinic found that intrinsic factors like self-efficacy, personal innovativeness, and performance expectancy positively related to mHealth adoption by physicians, whereas technology anxiety negatively related to adoption behaviour. Effort expectancy is not significant, indicating that m-Health adoption is driven by usefulness and result rather than convenience. If the expertise is not easily available, the physician's best interest for the patient may often drive them to adopt m-Health.

Perception of physicians towards electronic prescription system and associated factors at resource limited setting 2021: Cross sectional study

Introduction

The healthcare industry is increasingly concerned about medical errors, which are the leading cause of death worldwide and also compromise patient safety. This medical error is even more serious in developing countries where healthcare is not supported by technology. Because of the traditional paper-based prescription system, Ethiopia has an overall medication prescribing error rate of 58.07% that could be avoided if an electronic prescription system was in place. Therefore, this study aims to assess physicians’ perceptions towards electronic prescription implementation.

Methods

From February 1 to April 5, 2021, an institution-based cross-sectional study was conducted among physicians working in public hospitals in the Amhara region. 384 physicians were selected using a simple random sampling method. The data was collected using a self-administered questionnaire and analysed using SPSS, version 21. To assess factors associated with perception among physicians, a binary and multivariable logistic regression analysis were performed. A P.05 value, at a 95% confidence interval, was considered statistically significant. The validity of the questionnaire was determined based on expert opinion, as well as its reliability was determined by calculating the value of Cronbach alpha (α = .78).

Results

In this study, 231 (76.5%) of study participants had a positive perception of electronic prescription. Around 70.8% had more than 5 years of computer usage experience. Nearly 90% of participants claimed that their prescriptions were legible; however, 89% believe that paper-based prescriptions are prone to error. According to multivariable logistic regression analysis, technical skill [AOR] 4.7, 95% confidence interval [CI] (1.27–17.41), good internet access (AOR 2.82, % CI 1.75–4.54), and perceived usefulness of e-prescription system (AOR 3.31, 95% CI 1.01–12.12) were significantly associated with perception.

Conclusions

The majority of respondents have a positive perception of electronic prescription. The most notable factors associated with physician perception were organizational factors, internet access, perceived usefulness of the system, and technical skill.

Frameworks for implementation, uptake and use of digital health interventions in ethnic minority populations: a scoping review using cardiometabolic disease as a case study. (Preprint)

Background

Digital health interventions have become increasingly common across health care, both before and during the COVID-19 pandemic. Health inequalities, particularly with respect to ethnicity, may not be considered in frameworks that address the implementation of digital health interventions. We considered frameworks to include any models, theories, or taxonomies that describe or predict implementation, uptake, and use of digital health interventions.

Objective

We aimed to assess how health inequalities are addressed in frameworks relevant to the implementation, uptake, and use of digital health interventions; health and ethnic inequalities; and interventions for cardiometabolic disease.

Methods

SCOPUS, PubMed, EMBASE, Google Scholar, and gray literature were searched to identify papers on frameworks relevant to the implementation, uptake, and use of digital health interventions; ethnically or culturally diverse populations and health inequalities; and interventions for cardiometabolic disease. We assessed the extent to which frameworks address health inequalities, specifically ethnic inequalities; explored how they were addressed; and developed recommendations for good practice.

Results

Of 58 relevant papers, 22 (38%) included frameworks that referred to health inequalities. Inequalities were conceptualized as society-level, system-level, intervention-level, and individual. Only 5 frameworks considered all levels. Three frameworks considered how digital health interventions might interact with or exacerbate existing health inequalities, and 3 considered the process of health technology implementation, uptake, and use and suggested opportunities to improve equity in digital health. When ethnicity was considered, it was often within the broader concepts of social determinants of health. Only 3 frameworks explicitly addressed ethnicity: one focused on culturally tailoring digital health interventions, and 2 were applied to management of cardiometabolic disease.

Conclusions

Existing frameworks evaluate implementation, uptake, and use of digital health interventions, but to consider factors related to ethnicity, it is necessary to look across frameworks. We have developed a visual guide of the key constructs across the 4 potential levels of action for digital health inequalities, which can be used to support future research and inform digital health policies.

Willingness to Receive mHealth Messages Among Diabetic Patients at Mizan Tepi University Teaching Hospital: Implications for Digital Health

BACKGROUND

The growing access and use of mobile technology provide new tools for diabetic care and management. Mobile-based technology (mHealth) is considered as a useful tool to deliver healthcare services as a makeshift alternative for consultations and follow-up of diabetic patients. Therefore, this study aimed to scrutinize the willingness to receive mHealth messages and its associated factors among diabetic patients at Mizan Tepi University Teaching Hospital (MTUTH).

METHODS

A cross-sectional study was conducted among two hundred thirty-three diabetic patients. Data were collected using a structured and pre-tested interviewer-administered questionnaire. Epidata manager and SPSS software were used to enter and analyze the data, respectively. Multivariable logistic regression analysis was carried out to identify the independent factors associated with patients' willingness to receive mHealth messages.

RESULTS

Two hundred and thirty-three patients participated in this study with a 95% response rate. Majority of the patients (213, 91.4%) had a mobile phone. Among those who had mobile phones, 59.1%, (95% CI: 48-64) of patients were willing to receive mHealth messages from providers, if they were offered the opportunity. In the multivariable binary logistic regression analysis, monthly income >3000 ETB (AOR = 2.43; 95% CI (1.36-3.81)), owning smartphone (AOR = 3.85; 95% CI (1.67-4.89)), internet access in their mobile phone (AOR = 2.74; 95% CI (1.42-4.61)), perceived usefulness (AOR = 4.66; 95% CI (2.38-6.83)) and perceived ease to use (AOR = 3.87; 95% CI (1.57-5.46)) were identified as significant factors associated with diabetic patients' willingness to receive mHealth messages.

CONCLUSION

A high proportion of patients who had mobile phones were willing to receive mHealth messages. Monthly income, type of mobile phone, access to the internet on the mobile phone, perceived ease of use, and perceived usefulness were associated with willingness to receive mHealth messages. Therefore, focusing on these factors could provide insight for designing and implementing mHealth messages for diabetic patients.

Internet Use, Electronic Health Literacy, and Hypertension Control among the Elderly at an Urban Primary Care Center in Thailand: A Cross-Sectional Study

This study aimed to explore the internet usage and electronic health literacy (eHL) among adults aged 60 and older with hypertension and to explore the associations between eHL and blood pressure control. A cross-sectional survey was conducted at an out-patient primacy care clinic in the urban city center of Chiang Mai, Thailand. eHL was measured using the eHealth Literacy Scale (eHEALS). Logistic regression was used to identify the association between eHL and blood pressure, adjusting for age and sex as a priori confounders and key sociodemographic factors previously identified in univariable analysis. A total of 110 older adult patients with a history of diagnosed hypertension agreed to participate. The mean age of the participants was 67 years old. Fifty-six participants (50.9%) had used the internet in their lifetime. Among internet users, 37 out of 56 participants (66%) could be classified as having high eHL. However, there was insufficient evidence for associations among internet use, eHL and hypertension control. This result potentially creates new opportunities for eHealth education and interventions. Efforts to produce centralized clear, reliable health information targeting this demographic would be worthwhile to help manage chronic diseases such as hypertension in Thailand in the future.

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.

Development of an Instrument for Assessing the Maturity of Citizens for Consumer Health Informatics in Developing Countries: The Case of Chile, Ghana, and Kosovo

OBJECTIVE

 We aimed to develop a survey instrument to assess the maturity level of consumer health informatics (ConsHI) in low-middle income countries (LMIC).

METHODS

 We deduced items from unified theory of acceptance and use of technology (UTAUT), UTAUT2, patient activation measure (PAM), and ConsHI levels to constitute a pilot instrument. We proposed a total of 78 questions consisting of 14 demographic and 64 related maturity variables using an iterative process. We used a multistage convenient sampling approach to select 351 respondents from all three countries.

RESULTS

 Our results supported the earlier assertion that mobile devices and technology are standard today than ever, thus confirming that mobile devices have become an essential part of human activities. We used the Wilcoxon Signed-Rank Test (WSRT) and item response theory (IRT) to reduce the ConsHI-related items from 64 to 43. The questionnaire consisted of 10 demographic questions and 43 ConsHI relevant questions on the maturity of citizens for ConsHI in LMIC. Also, the results supported some moderators such as age and gender. Additionally, more demographic items such as marital status, educational level, and location of respondents were validated using IRT and WSRT.

CONCLUSION

 We contend that this is the first composite instrument for assessing the maturity of citizens for ConsHI in LMIC. Specifically, it aggregates multiple theoretical models from information systems (UTAUT and UTAUT2) and health (PAM) and the ConsHI level.

A model of digital health communication media use during the Covid-19 pandemic

Purpose

This research aims to develop and test a model of digital health communication media (DHCM) use for healthy food information – DHCM usage – during the Covid-19 pandemic. More specifically, this research investigated the simultaneous effects of perceived threat of Covid-19, e-health literacy, attitude toward DHCM usage, knowledge toward DHCM usage, facilitating conditions and information quality on the DHCM usage.

Design/methodology/approach

The empirical data were collected through a survey. The respondents of the survey are 192 DHCM users who lived in Tangerang Regency. Structural equation modelling (SEM) analysis was performed.

Findings

The DHCM usage during the Covid-19 pandemic is significantly affected by the attitude towards the DHCM usage and the facilitating conditions. However, the DHCM usage during the Covid-19 pandemic is not significantly affected by the perceived threat of Covid-19, e-health literacy, information quality and knowledge of the DHCM usage.

Research limitations/implications

This research was conducted only in Tangerang Regency and employed a purposive sampling technique. Future research should be conducted in other contexts to examine the stability of the research findings.

Practical implications

In order to improve DHCM usage for healthy food information, it is important for building a positive attitude towards DHCM usage and ensuring the availability of the facilitating conditions.

Originality/value

This paper is the first that develops and tests a model of DHCM usage for healthy food information during the Covid-19 pandemic.

Elderly and middle-aged intention to use m-health services: an empirical evidence from a developing country

Purpose

m-health services for different age groups are becoming an emerging field in the health-care industry, especially in low-resource environments such as developing countries such as Bangladesh. Hence, this study’s primary aim is to identify the factors that influence the middle-aged and elderly’s intention to use m-health services.

Design/methodology/approach

This study applied the extended version of the unified theory of acceptance and use of technology to explore middle-aged and elderly’s intention to use m-health services. There were 235 respondents, of which 123 (52.34%) were in the middle-aged group, whereas 112 (47.66%) were in the older group. Both groups were found to have more male participants than female participants. The partial least square (PLS) method was used to analyze data.

Findings

The study found that performance expectancy, effort expectancy, facilitating condition, technological anxiety and resistance to change (p < 0.05) had a significant influence on middle-aged intention to use m-health services. Social influence and perceived physical condition (p > 0.05) had no significant effect on middle-aged intention to use m-health services. On the other hand, performance expectancy, effort expectancy, facilitating condition and resistance to change (p <* 0.05) significantly influenced the elderly’s intention to use m-health services. However, the social impact of perceived physical condition and technological anxiety (p > 0.05) had no significant effect on the elderly’s intention to use m-health services.

Originality/value

A good number of studies are available in the current literature, examining the factors adoption of m-health services in both developed and developing economy context. However, very few studies examine the factors that influence behavioral intention to use m-health services concerning the two different age groups, such as middle-aged and elderly. Moreover, to the best of the authors’ knowledge, there is a shortage of literature on this topic built on the comparative analysis between the two age groups.

Evaluating the Readiness of Mobile Technology with Respect to e-Heath for Medication in Saudi Arabia: An Integrative Perspective

Objective

The objective of this study was to evaluate the readiness of Saudi Arabian patients towards the adoption of the e-health system through the use of mobile phones.

Methods

In this research, a cross-sectional survey was carried out using a self-administered structured questionnaire. According to the results, 354 people viewed the questionnaire and 129 respondents were selected to assess the adoption of the e-health system in Saudi Arabia. The data were collected during February–March 2020.

Results

More than half of the respondents (63.6%) were women and almost half of the participants (48.0%) were married. Most of the surveyed patients suffered from cardiovascular diseases and diabetes. Almost all the participants (99.0%) had their personal mobile phone and used the Internet on these devices. Most of the participants did not trust or believe in online health services or online medical consultations and did not spend money on contracting health services through mobile phones. It is suggested that the lack of motivation to adopt the e-health system may be due to fear of privacy violations, fear of loss of personal data and information, lack of technical support, and mistrust in doctors who frequently use their cell phones to distract themselves during work-hours.

Conclusion

The results of this study revealed that the population of Saudi Arabia is reluctant to adopt the electronic e-health system promoted in the Saudi Vision 2030 strategic plan. To change this behavior, it is necessary to develop awareness campaigns and strategies that suggest the importance of using e-heath in the Saudi Arabian healthcare system. Additionally, it is essential that the network administrator implement procedures to protect the confidentiality and security of patients’ medical records.

The Mobile Health Readiness of People Receiving In-Center Hemodialysis and Home Dialysis

BACKGROUND AND OBJECTIVES

Mobile health is the health care use of mobile devices, such as smartphones. Mobile health readiness is a prerequisite to successful implementation of mobile health programs. The aim of this study was to examine the status and correlates of mobile health readiness among individuals on dialysis.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

A cross-sectional 30-item questionnaire guided by the Khatun mobile health readiness conceptual model was distributed to individuals on dialysis from 21 in-center hemodialysis facilities and 14 home dialysis centers. The survey assessed the availability of devices and the internet, proficiency, and interest in using mobile health.

RESULTS

In total, 949 patients (632 hemodialysis and 317 home dialysis) completed the survey. Of those, 81% owned smartphones or other internet-capable devices, and 72% reported using the internet. The majority (70%) reported intermediate or advanced mobile health proficiency. The main reasons for using mobile health were appointments (56%), communication with health care personnel (56%), and laboratory results (55%). The main reported concerns with mobile health were privacy and security (18%). Mobile health proficiency was lower in older patients: compared with the 45- to 60-years group, respondents in age groups <45, 61-70, and >70 years had adjusted odds ratios of 5.04 (95% confidence interval, 2.23 to 11.38), 0.39 (95% confidence interval, 0.24 to 0.62), and 0.22 (95% confidence interval, 0.14 to 0.35), respectively. Proficiency was lower in participants with Hispanic/Latinx ethnicity (adjusted odds ratio, 0.49; 95% confidence interval, 0.31 to 0.75) and with less than college education (adjusted odds ratio for "below high school," 0.09; 95% confidence interval, 0.05 to 0.16 and adjusted odds ratio for "high school only," 0.26; 95% confidence interval, 0.18 to 0.39). Employment was associated with higher proficiency (adjusted odds ratio, 2.26; 95% confidence interval, 1.18 to 4.32). Although home dialysis was associated with higher proficiency in the unadjusted analyses, we did not observe this association after adjustment for other factors.

CONCLUSIONS

The majority of patients on dialysis surveyed were ready for, and proficient in, mobile health. CLINICAL TRIAL REGISTRY NAME AND REGISTRATION NUMBER DIALYSIS MHEALTH SURVEY,: NCT04177277.

The Applicability of the Modified Technology Acceptance Model (TAM) on the Sustainable Adoption of eHealth Systems in Resource-Limited Settings

BACKGROUND

The implementation of eHealth systems with a trial-and-error approach is very expensive and unsuccessful. So, this study aims to examine the constructs and relationships of the modified technology acceptance model (TAM) to determine whether it can be applied to assess health professional's behavioral intention to adopt eHealth systems in resource-limited settings or not.

METHODS

The institutional-based cross-sectional study design was conducted among a total of 384 healthcare professionals in referral hospitals of Amhara regional state, Ethiopia. Self-administered questionnaire was used to collect the data, and the data were entered using Epi-info version 7 and the descriptive data were analyzed using SPSS version 25. Structural equation modeling, using AMOS 22, was also applied to describe and validate the degree of relationships between variables.

RESULTS

The findings of the structural equation modeling (SEM) indicate that perceived usefulness has a significant influence on attitude (β =0.298, P<0.01) and intention to use eHealth (β =0.387, P<0.01). Perceived ease of use has significant influence on perceived usefulness (β=0.385, P<0.05) and attitude (β=0.347, P<0.05) and intention to use eHealth (β=0.339, P<0.01). Technical infrastructure has significant influence on attitude (β =0.412, P<0.01) and intention to use eHealth (β =0.355, P<0.01). The staffs IT experience has a significant influence on perceived usefulness (β =0.595, P<0.01) and attitude (β =0.267, P<0.05), but the effect of IT experience on the intention to use eHealth was not significant. Among all the constructs, healthcare professionals attitude towards eHealth showed the strongest effect on the intention to use eHealth systems (β = 0.52, P<0.01).

CONCLUSION

Overall, this model describes 56.2% of the variance in behavioral intention to use eHealth systems. Therefore, the implementers should give priority in enhancing the organizations technical infrastructure, staff's IT skill, and their attitude towards eHealth by giving continuous support.

Digital Health and Inequalities in Access to Health Services in Bangladesh: Mixed Methods Study

Background

Globally, the rapid growth of technology and its use as a development solution has generated much interest in digital health. In line with global trends, Bangladesh is also integrating technology into its health system to address disparities. Strong political endorsement and uptake of digital platforms by the government has influenced the rapid proliferation of such initiatives in the country. This paper aims to examine the implications of digital health on access to health care in Bangladesh, considering who uses electronic devices to access health information and services and why.

Objective

This study aims to understand how access to health care and related information through electronic means (digital health) is affected by sociodemographic determinants (ie, age, gender, education, socioeconomic status, and personal and household ownership of mobile phones) in a semiurban community in Bangladesh.

Methods

A cross-sectional survey of 854 households (between October 2013 and February 2014) and 20 focus group discussions (between February 2017 and March 2017) were conducted to understand (1) who owns electronic devices; (2) who, among the owners, uses these to access health information and services and why; (3) the awareness of electronic sources of health information; and (4) the role of intermediaries (family members or peers who helped to look for health information using electronic devices).

Results

A total of 90.3% (771/854) of households (471/854, 55.2% of respondents) owned electronic devices, mostly mobile phones. Among these, 7.2% (34/471) used them to access health information or services. Middle-aged (35-54 years), female, less (or not) educated, and poorer people used these devices the least (α=.05, α is the level of significance). The lack of awareness, discomfort, differences with regular care-seeking habits, lack of understanding and skills, and proximity to a health facility were the main reasons for not using devices to access digital health.

Conclusions

Although influenced by sociodemographic traits, access to digital health is not merely related to device ownership and technical skill. Rather, it is a combination of general health literacy, phone ownership, material resources, and technical skill as well as social recognition of health needs and inequity. This study’s findings should serve as a basis for better integrating technology within the health system and ensuring equitable access to health care.

Technology Acceptance in Mobile Health: Scoping Review of Definitions, Models, and Measurement

BACKGROUND

Designing technologies that users will be interested in, start using, and keep using has long been a challenge. In the health domain, the question of technology acceptance is even more important, as the possible intrusiveness of technologies could lead to patients refusing to even try them. Developers and researchers must address this question not only in the design and evaluation of new health care technologies but also across the different stages of the user's journey. Although a range of definitions for these stages exists, many researchers conflate related terms, and the field would benefit from a coherent set of definitions and associated measurement approaches.

OBJECTIVE

This review aims to explore how technology acceptance is interpreted and measured in mobile health (mHealth) literature. We seek to compare the treatment of acceptance in mHealth research with existing definitions and models, identify potential gaps, and contribute to the clarification of the process of technology acceptance.

METHODS

We searched the PubMed database for publications indexed under the Medical Subject Headings terms "Patient Acceptance of Health Care" and "Mobile Applications." We included publications that (1) contained at least one of the terms "acceptability," "acceptance," "adoption," "accept," or "adopt"; and (2) defined the term. The final corpus included 68 relevant studies.

RESULTS

Several interpretations are associated with technology acceptance, few consistent with existing definitions. Although the literature has influenced the interpretation of the concept, usage is not homogeneous, and models are not adapted to populations with particular needs. The prevalence of measurement by custom surveys suggests a lack of standardized measurement tools.

CONCLUSIONS

Definitions from the literature were published separately, which may contribute to inconsistent usage. A definition framework would bring coherence to the reporting of results, facilitating the replication and comparison of studies. We propose the Technology Acceptance Lifecycle, consolidating existing definitions, articulating the different stages of technology acceptance, and providing an explicit terminology. Our findings illustrate the need for a common definition and measurement framework and the importance of viewing technology acceptance as a staged process, with adapted measurement methods for each stage.

A model for evaluating eHealth preparedness – a case study approach

Purpose

This paper aims to validate an initially developed e-Health readiness assessment model.

Design/methodology/approach

The authors thematically analysed an initial qualitative data collected and used the outcome to develop survey instruments for this study. To collect the quantitative data, the authors used the drop and collect survey approach given the research setting. The quantitative data was analysed using factor and regression analyses of SPSS 23 in which hypotheses formulated were tested.

Findings

The results suggest that the model [R2 = 0.971; F (5, 214) = 1414.303], which is made up of readiness assessment factors (constructs) and measuring tools explain about 97% of the variance of the overall health information technology/e-Health adoption readiness at Komfo Anokye Teaching Hospital. The measuring tools were reliable for assessing the composite variables (constructs): technology readiness; operational resource readiness; organizational and cultural readiness; regulatory and policy readiness; and core readiness, which have significant influence on eHealth adoption readiness assessment..

Originality/value

This study has successfully validated empirically developed eHealth readiness assessment model with complete reliable indicators given that existing eHealth readiness assessment models have not been effective due to a general lack of standard indicators for measuring assessment factors. The study also contributes to the growing research on the adoption of information technology/systems in health-care environment using the Technology–Organization–Environment framework.

Understanding continuance usage intention of mHealth in a developing country

Purpose

This study aims to understand the factors affecting the continuance usage intention (CUI) of mHealth among the rural elderly.

Design/methodology/approach

An integrated model was proposed with the constructs derived from multiple models such as the unified theory of acceptance and use of technology, information system success model and expectation confirmation model. Data were collected from 400 participants who had prior experiences with mHealth services in Bangladesh. The research model was tested using the partial least squares method based upon structural equation modelling.

Findings

The findings indicated that system quality, performance expectancy, facilitating conditions and social influence were significant to the degree of confirmation and ultimately affect satisfaction and CUI. Surprisingly, service quality and information quality were insignificant.

Research limitations/implications

This study has added in the field of knowledge by contributing some new thoughts and interpretations of continuance usage modelling for mHealth services. The findings may become beneficial for the government agencies, policymakers, mHealth systems developers and service providers.

Originality/value

As limited research was found on CUI of mHealth in the integrated view of rural elderly’s value, this research contributes to the extant literature by categorizing key factors that might support to proliferate the continuance usage of this service. Moreover, the contextualization of the related variables and integration of the existing model is theoretically original. Furthermore, because of a generic approach, the findings could be easily modified to assist other developing countries in the planning and up-take of mHealth.

Lessening barriers to healthcare in rural Ghana: providers and users' perspectives on the role of mHealth technology. A qualitative exploration

BACKGROUND

Key barriers to healthcare use in rural Ghana include those of economic, social, cultural and institutional. Amid this, though rarely recognised in Ghanaian healthcare settings, mHealth technology has emerged as a viable tool for lessening most healthcare barriers in rural areas due to the high mobile phone penetration and possession rate. This qualitative study provides an exploratory assessment of the role of mHealth in reducing healthcare barriers in rural areas from the perspective of healthcare users and providers.

METHOD

Semi-structured interviews were conducted with 30 conveniently selected healthcare users and 15 purposively selected healthcare providers within the Birim South District in the Eastern Region of Ghana between June 2017 and April 2018. Data were thematically analysed and normative standpoints of participants were presented as quotations.

RESULTS

The main findings were that all the healthcare users had functioning mobile phones, however, their knowledge and awareness about mHealth was low. Meanwhile, rural health care users and providers were willing to use mHealth services involving phone call in the future as they perceived the technology to play an important role in lessening healthcare barriers. Nevertheless, factors such as illiteracy, language barrier, trust, quality of care, and mobile network connectivity were perceived as barriers associated with using mHealth in rural Ghana.

CONCLUSION

The support for mHealth service is an opportunity for the development of synergistic relationship between health policy planners and mobile network companies in Ghana to design efficient communication and connectivity networks, accessible, localised, user-friendly and cost-effective mobile phone-based health programmes to assist in reducing healthcare barriers in rural Ghana.

Investigating usability of mobile health applications in Bangladesh

Background

Lack of usability can be a major barrier for the rapid adoption of mobile services. Therefore, the purpose of this paper is to investigate the usability of Mobile Health applications in Bangladesh.

Method

We followed a 3-stage approach in our research. First, we conducted a keyword-based application search in the popular app stores. We followed the affinity diagram approach and clustered the found applications into nine groups. Second, we randomly selected four apps from each group (36 apps in total) and conducted a heuristic evaluation. Finally, we selected the highest downloaded app from each group and conducted user studies with 30 participants.

Results

We found 61% usability problems are catastrophe or major in nature from heuristic inspection. The most (21%) violated heuristic is aesthetic and minimalist design. The user studies revealed low System Usability Scale (SUS) scores for those apps that had a high number of usability problems based on the heuristic evaluation. Thus, the results of heuristic evaluation and user studies complement each other.

Conclusion

Overall, the findings suggest that the usability of the mobile health apps in Bangladesh is not satisfactory in general and could be a potential barrier for wider adoption of mobile health services.

Adoption intention and usage behavior of mHealth services in Bangladesh and China

Purpose

The purpose of this paper was to explore the comparative influential factors affecting the behavioral intention and actual usage of mHealth services in two distinct national environments, i.e. China and Bangladesh, in relation to the international expansion of mHealth services.

Design/methodology/approach

In this study, widely accepted Unified Theory of Acceptance and Use of Technology (UTAUT) with two additional variables, i.e. Perceived Reliability and Price Value have been selected as a theoretical framework. Primary data were collected from existing mHealth users among generation Y in both China and Bangladesh. A total of 296 and 250 questionnaires were deemed as usable for data analysis for Bangladesh and China, respectively.

Findings

Performance expectancy and social influence had significant impact on the adoption intention of mHealth services for both countries. Effort expectancy and price value were insignificant factors for Bangladesh, whereas facilitating condition and perceived reliability were insignificant for China.

Practical implications

The insights from this study could benefit mHealth services providers and those policymakers who seek to enter the Chinese and the Bangladeshi healthcare market. The dimensions identified in the study are based on a full assessment of mHealth usages experiences. Global service providers can use the dimensions identified by the paper to better assess their service performance on an international level.

Originality/value

The paper is unique in that it is one of the first cross-country examinations of influential factors affecting the adoption of mHealth services in two different countries. This study confirms the applicability of extended UTAUT model in the context of mHealth services among the generation Y in developing countries such as China and Bangladesh.

Testing mHealth solutions at the last mile: insights from a study of technology-assisted community health referrals in rural Kenya

BACKGROUND

mHealth technologies are already disrupting conventional healthcare delivery by making innovative solutions more accessible in terms of reach and price across reach and price across the developing world. However, much less has been documented on the process of mHealth innovation introduction in the context of rural communities of Africa. Pending still is the widespread adoption of standards and the removal of barriers to introduction, testing and scale. This paper documents the innovation process of technology introduction, results and lessons learned through a case study of two mHealth initiatives: closed-loop referrals for maternal and child health; and HIV self-testing. Both initiatives were implemented and evaluated in Kisii County, Kenya by Living Goods.

METHODS

Living Goods applied an innovation framework to introduce and evaluate two interventions integrated into the Living Goods Smart Health app, a smartphone-based digital health application designed to carry out household registration, assessment, and diagnosis at community level. Community health workers (CHWs) used digitally assisted, standardized Ministry of Health algorithms to assess and refer clients to the nearest health facility for diagnosis confirmation and treatment as appropriate. Routine data as well as periodic household surveys were captured to incorporate performance data and outcomes into activity management. A quasi-experimental evaluation was carried out using a Propensity Score Matching (PSM) methodology to evaluate intervention arms for each intervention.

RESULTS

Findings suggest that the initiatives increased the frequency of visits to households with participants in the treatment groups being more likely to have been visited more than six times within the last six months. The interventions contributed in part to an increase in the frequency of CHW follow-up visits within the treatment group. Attitudes of trust and confidence in CHWs were high but limited to referral services and not to diagnostic and curative services.

CONCLUSIONS

The innovation process effectively positioned and tested at community level the two interventions to address key barriers to service delivery acceptance and uptake. Despite extensive pre-testing and field iterations to adapt the solutions to the local context, behavioral and technology barriers persisted. The study highlights important implications for both innovators and service providers: technology introduction and adaptation at community level requires multiple, rapid iteration loops to ensure product refinement and user-acceptance; behavioral assessments of acceptability require a wholistic approach to ensure effective alignment of senders, receivers and trusted intermediaries of novel services.

Improving health equity for ethnic minority women in Thai Nguyen, Vietnam: qualitative results from an mHealth intervention targeting maternal and infant health service access

Background

Ethnic minority women (EMW) in Vietnam experience disproportionately high infant and maternal mortality rates due to low social status, poverty and remoteness from health centres. This project piloted and evaluated a low-cost mobile health (mHealth) intervention called mMom utilizing behaviour change communication (BCC) to improve access to maternal, newborn and child health (MNCH) services and health equity among EMW living in remote areas.

Methods

The mMom intervention built an integrated mHealth platform which sent timely MNCH information and BCC text messages to participants, and engaged health workers towards increasing their interaction and building demand for quality natal care. Mid-term and final qualitative evaluations were conducted to assess the intervention's acceptability and impact.

Results

In evaluations, all participants expressed satisfaction with the quality, timeliness and convenience of the messages, and health workers reported increased efficiency and quality of care. The use of BCC increased care-seeking from EMW and strengthened relationships with health providers.

Conclusion

The mMom project demonstrated the acceptability of mHealth in a remote Vietnamese region with a high proportion of disadvantaged EMW. The messages promoted increased contact between participants and health providers, which holds potential to address the marginalization of EMW from the health system.

Keywords

behaviour change communication, eHealth, ethnic minorities, health equity, mHealth, MNCH, mobile health, Vietnam.

Knowledge, attitude, and use of mHealth technology among students in Ghana: A university-based survey

Background

Interest in mHealth interventions, defined as the use of mobile phones to access healthcare is increasingly becoming popular globally. Given its technology-based applications, university students may be key clients of the mHealth adoption but studies are rare in sub-Saharan Africa. This study provides a snapshot and baseline evidence on knowledge, attitude and use of mHealth among university students in Ghana.

Methods

Using a self-administered questionnaire, we collected data between April and June 2017 from 963 randomly sampled undergraduate students at the Kwame Nkrumah University of Science and Technology (KNUST). Pearson’s Chi-square (χ²) test assessed the differences between variables whilst  logistic regression models estimated the independent predictors of use of mHealth with p < 0.05 as significant.

Results

Knowledge on mHealth was moderately high. Specifically, more than half of the sample reported awareness of mHealth although the prevalence of use of mHealth stood at 51%. Logistic regressions revealed that mHealth use was positively associated with respondents’ year (second year: OR = 1.704, 95% CI: 1.185–2.452, and third year: OR = 1.528, 95% CI: 1.060–2.202), and monthly income (OR:3.112, 95%CI: 1.180-8.211). However, ethnicity [(OR = 0.761, 95% CI (0.580–0.997)] was negatively associated with the use of mHealth technology.

Conclusion

Findings suggest that knowledge of mHealth among university students is low. Policy and public health interventions for urgent awareness creation and promotion of use of mHealth as well as its possible integration into the mainstream healthcare system in Ghana are timely.

A Model for Assessing Necessary Conditions for Rural Health Care's Mobile Health Readiness: Qualitative Assessment of Clinician-Perceived Barriers

BACKGROUND

Mobile health (mHealth) technology dissemination has penetrated rural and urban areas alike. Yet, health care organization oversight and clinician adoption have not kept pace with patient use. mHealth could have a unique impact on health and quality of life for rural populations. If organizations are prepared to manage mHealth, clinicians may improve the quality of care for their patients, both rural and urban. However, many organizations are not yet prepared to prescribe or prohibit third-party mHealth technologies.

OBJECTIVE

This study explored organizational readiness for rural mHealth adoption, the use of patient-reported data by clinical care teams, and potential impact on improving rural health care delivery.

METHODS

Semistructured, open-ended interviews were used to investigate clinicians' current practices, motivators, and perceived barriers to their use of mHealth technologies in rural settings.

RESULTS

A total of 13 clinicians were interviewed, and 53.8% (7/13) reported encouraging use of mHealth apps or wearable devices with rural patients. Perceived barriers to adoption were categorized into three primary themes: (1) personal (clinician), (2) patient, and (3) organizational. Organizational was most prominent, with subcodes of time, uniformity, and policy or direction. Thematic analysis revealed code-category linkages that identify the complex nature of a rural health care organization's current climate from a clinician's perspective. A thematic map was developed to visualize the flow from category to code. Identified linkages guided the development of a refined rural mHealth readiness model.

CONCLUSIONS

Clinicians (including physicians) have limited time for continuing education, research, or exploration of emerging technologies. Clinicians are motivated to learn more, but they need guidance through organization-led directives. Rural health care institutions should consider investing in mHealth analysis, tool development, and formal recommendations of sanctioned tools for clinicians to use with patients.

How Resource Scarcity and Accessibility Affect Patients' Usage of Mobile Health in China: Resource Competition Perspective

BACKGROUND

The last decade has witnessed many achievements in China's health care industry, but the industry still faces major challenges among which the uneven distribution of medical resources and the imbalance between supply and demand are the most pressing problems. Although mobile health (mHealth) services play a significant role in mitigating problems associated with health care delivery, their adoption rates have been low.

OBJECTIVE

The objective of this study was to explore the impact of resource scarcity and resource accessibility on the adoption of mHealth from the perspective of resource competition, to examine the concerning factors, and to provide a theoretical basis for promoting mHealth in China.

METHODS

We used 229,516 original registration records of outpatients to conduct an empirical analysis to examine the adoption of mHealth services from the perspective of resource competition.

RESULTS

The adoption rate of mobile services for outpatients was low, accounting for only 31.5% (N=71,707). The empirical results indicated that resource scarcity (beta=.435, P=.01) and accessibility (beta=-.134, P=.02) have a significant impact on the adoption of mHealth. In addition, gender (beta=.073, P=.01) and age (beta=-.009, P<.001) are significantly related to adoption of mHealth. Experience with mHealth has a moderating role in the relationship between resource scarcity (beta=-.129, P=.02), accessibility (beta=.138, P=.04), and adoption of mHealth.

CONCLUSIONS

In this study we demonstrate that the external environment (resource scarcity and resource accessibility) has a significant impact on the adoption of mHealth. This study also demonstrates that experience with mHealth has a moderating role in the relationship between the elements of the external environment. Finally, we confirm that mHealth is a key factor in the delivery and allocation of medical resources and provide a theoretical basis for government agencies to develop policies on mHealth.

Acceptability and Attitude towards a Mobile-Based Home Exercise Program among Stroke Survivors and Caregivers: A Cross-Sectional Study

Background

Stroke is a leading cause of disability and requires continued care after hospital discharge. Mobile-based interventions are suitable to reduce the cost of stroke rehabilitation and facilitate self-management among stroke survivors. However, before attempting to use mobile-based home exercise program, it is crucial to recognize the readiness of stroke survivors and their caregivers to opt for such interventions.

Objective

To assess the acceptability and attitude towards a mobile-based home exercise program among stroke survivors and their primary caregivers.

Methods

A cross-sectional study was conducted among 102 participants to understand their attitude and acceptability towards mobile-based home exercise program. A validated 10-item questionnaire was adapted for the study. The questions which assessed the attitude were rated on a three-point Likert scale, with three denoting agree and one denoting disagree. The acceptability was assessed by their willingness to opt for a mobile-based home program services. A Chi-square analysis and cross-tabulation were performed to test differences between caregivers and patients. A logistic regression was performed to determine the effects of age, gender, and mobile phone on acceptability.

Results

Ninety-two percent of caregivers and 90% of patients showed willingness to opt for mobile-based intervention. Majority of the participants showed a positive attitude towards this mode of treatment. There was no difference in the attitude noted among caregivers and patients (p>0.05) towards mobile-based intervention.

Conclusion

The stroke survivors and caregivers welcomed the concept of mobile-based home exercise program even in a low-resource settings, but further studies to understand treatment and cost-effectiveness of this technology among the stroke survivors would lead to better implementation.

Development of an evidence-based e-health readiness assessment framework for Uganda

BACKGROUND

While e-health readiness assessment is vital to the successful implementation of e-health innovations, there is little published guidance (i.e. e-health readiness assessment frameworks (eHRAFs)) for institutions and countries.

OBJECTIVE

To develop an evidence-based and locally relevant eHRAF for Uganda.

METHOD

A list of possible e-health readiness domains and constructs was developed through a structured review of the e-health literature. This list was first refined using author experience, insight and reflection. Based on this refined list, an eHRAF questionnaire was developed, which was initially pilot tested for face and content validity. Thereafter, it was distributed to 13 purposively selected study participants who were Ugandan e-health experts from the fields of health, information and communications technology (ICT) and academia. The questionnaire was discussed in a focus group setting for consensus input, where study participants confirmed, rejected or revised proposed domains and constructs suitable to guide e-health readiness assessment at either the national or site-specific level within Uganda.

RESULTS

Of 148 identified literature resources, 13 met inclusion criteria. A subjective review highlighted 11 frequently used e-health domains. Further reflection reduced these to nine domains, which were shared with study participants by means of the questionnaire. Based upon prior use of, and familiarity with, a management tool (PESTEL), participants' consensus on factors essential for readiness assessment in Uganda was aligned with PESTEL's six domains: political, economic, sociocultural, technological, environmental, and legal and regulatory. The participants considered engagement, and core and societal readiness as optional domains. Based on this input, the authors developed a proposed eHRAF suitable for Uganda, comprised of domains, sub-domains and constructs.

CONCLUSION

The eHRAF developed in this research is an evidence-based framework (literature and cross-sectoral expert opinion) and consists of primary domains, sub-domains and constructs suitable for assessing e-health readiness in Uganda, either nationally or locally, prior to implementation of any e-health system. The process and principles may have utility in other countries.

IMPLICATIONS

A national, culturally relevant, context-specific Ugandan eHRAF could facilitate efficient and effective planning and implementation of new e-health programmes across the country and assist policymakers and legislators to develop consistent and reliable guidelines and regulations.

How and why front-line health workers (did not) use a multifaceted mHealth intervention to support maternal and neonatal healthcare decision-making in Ghana

Introduction

Despite increasing use of mHealth interventions, there remains limited documentation of 'how and why' they are used and therefore the explanatory mechanisms behind observed effects on beneficiary health outcomes. We explored 'how and why' an mHealth intervention to support clinical decision-making by front-line providers of maternal and neonatal healthcare services in a low-resource setting was used. The intervention consisted of phone calls (voice calls), text messaging (short messaging service (SMS)), internet access (data) and access to emergency obstetric and neonatal protocols via an Unstructured Supplementary Service Data (USSD). It was delivered through individual-use and shared facility mobile phones with unique Subscriber Identification Module (SIM) cards networked in a Closed User Group.

Methods

A single case study with multiple embedded subunits of analysis within the context of a cluster randomised controlled trial of the impact of the intervention on neonatal health outcomes in the Eastern Region of Ghana was performed. We quantitatively analysed SIM card activity data for patterns of voice calls, SMS, data and USSD. We conducted key informant interviews and focus group discussions with intervention users and manually analysed the data for themes.

Results

Overall, the phones were predominantly used for voice calls (64%), followed by data (28%), SMS (5%) and USSD (2%), respectively. Over time, use of all intervention components declined. Qualitative analysis showed that individual health worker factors (demographics, personal and work-related needs, perceived timeliness of intervention, tacit knowledge), organisational factors (resource availability, information flow, availability, phone ownership), technological factors (attrition of phones, network quality) and client perception of health worker intervention usage explain the pattern of intervention use observed.

Conclusion

How and why the mHealth intervention was used (or not) went beyond the technology itself and was influenced by individual and context-specific factors. These must be taken into account in designing similar interventions to optimise effectiveness.

Improving Sustainable Mobile Health Care Promotion: A Novel Hybrid MCDM Method

Identifying the key influencing factors that affected users’ adoption of sustainable mobile health care and improving alternative mobile health services continuously can help ordinary consumers (especially vulnerable populations) use extensive health resources cheaply and conveniently; which can increase the quality and equity of health services; so as to promote the sustainable development of medical resources. We integrated decision making trial and evaluation laboratory (DEMETEL)-based analytic network process (DANP) and a modified VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method to form a DDANPMV (DEMATEL+ DANP + Modified VIKOR) model to examine consumers’ adoption of mobile health care. This method was developed to not only help decision-makers evaluate alternative mobile health care and determine the best option, but also use to identify and improve the performance gap of alternative products with the goal of satisfying the aspirations of consumers. Four types of mobile health care products were analyzed. The results indicate that social norms; product image; and consumer trust are three key factors in consumer adoption. The results can guide policy design and implementation. The government and enterprises should improve mobile health care through these three aspects.

What Predicts Patients' Adoption Intention Toward mHealth Services in China: Empirical Study

Background

With the increasing concerns about the health of individuals in China and the development of information technology, mHealth enables patients to access health information and interact with doctors anytime and anywhere. Examining patients’ willingness to use mHealth is considered critical because its success depends on the adoption of patients.

Objective

The objective of our study was to explore the determinants of mHealth service adoption among Chinese patients using an extended technology acceptance model (TAM) with trust and perceived risks.

Methods

We conducted a questionnaire-based survey in 3 large hospitals in China and analyzed the data using structural equation modeling.

Results

The results corroborated that the proposed model fits well. Trust, perceived usefulness, and perceived ease of use positively correlated with mHealth service adoption. Privacy and performance risks negatively correlated with the patients’ trust and adoption intention toward mHealth services. In addition, patients’ age and chronic diseases can help predict their trust level and adoption intention toward mHealth, respectively.

Conclusions

We concluded that the TAM generally works in the context of mHealth adoption, although its significance has declined. In addition to technical factors, trust and perceived risks are critical for explaining mHealth service adoption among Chinese patients.

Identifying Barriers and Facilitators of 13 mHealth Projects in North America and Africa: Protocol for a 5-Year Implementation Science Study

Background

Although many mHealth interventions have shown efficacy in research, few have been effectively implemented and sustained in real-world health system settings. Despite this programmatic gap, there is limited conclusive evidence identifying the factors that affect the implementation and successful integration of mHealth into a health system.

Objective

The aim of this study is to examine the individual, organizational, and external level factors associated with the effective implementation of WelTel, an mHealth intervention designed to support outpatient medication adherence and engagement in care in Africa and North America.

Methods

We will adopt the Consolidated Framework for Implementation Research (CFIR) constructs for evaluation of mHealth implementation including a scoring and monitoring system. We will apply the adapted tool to identify facilitators and barriers to implementation of the WelTel mHealth intervention in order to determine how the technology platform is perceived, diffused, adapted, and used by different mHealth project teams and health system actors in Africa and North America. We will use a mixed-methods approach to quantitatively test whether the factors identified in the CFIR framework are associated with the successful uptake of the mHealth intervention toward implementation goals. We will triangulate these data through interviews and focus group discussion with project stakeholders, exploring factors associated with successful implementation and sustainment of these interventions.

Results

The development of the customized CFIR is finalized and currently is in pilot testing. The initial results of the use of the tool in those 13 implementations will be available in 2019. Continuous conference and peer- reviewed publications will be published in the coming years.

Conclusions

The results of this study will provide an in-depth understanding of individual, organizational, and external level factors that influence the successful implementation of mHealth in different health systems and geographic contexts over time. Via the tool’s unique scoring system connected to qualitative descriptors, these data will inform the most critical implementation targets and contribute to the tailoring of strategies that will assist the health system in overcoming barriers to implementation, and ultimately, improve treatment adherence and engagement in care.

Registered Report Identifier

RR1-10.2196/9633

m-Health Policy Readiness and Enabling Factors: Comparisons of Sub-Saharan Africa and Organization for Economic Cooperation and Development Countries

Background:As an innovative solution to poor access to care in low- and middle-income countries (LMICs), m-health has gained wide attention in the past decade.

Introduction:Despite enthusiasm from the global health community, LMICs have not demonstrated high uptake of m-health promoting policies or public investment.

Materials and Methods:To benchmark the current status, this study compared m-health policy readiness scores between sub-Saharan Africa and high-income Organization for Economic Cooperation and Development (OECD) countries using an independent two-sample t test. In addition, the enabling factors associated with m-health policy readiness were investigated using an ordinal logistic regression model. The study was based on the m-health policy readiness scores of 112 countries obtained from the World Health Organization Third Global Survey on e-Health.

Results:The mean m-health policy readiness score for sub-Saharan Africa was statistically significantly lower than that for OECD countries (p = 0.02). The enabling factors significantly associated with m-health policy readiness included information and communication technology development index (odds ratio [OR] 1.57; 95% confidence interval [CI] 1.12–2.2), e-health education for health professionals (OR 4.43; 95% CI 1.60–12.27), and the location in sub-Saharan Africa (OR 3.47; 95% CI 1.06–11.34).

Discussion:The findings of our study suggest dual policy goals for m-health in sub-Saharan Africa. First, enhance technological and educational support for m-health. Second, pursue global collaboration for building m-health capacity led by sub-Saharan African countries with hands-on experience and knowledge.

Conclusion:Globally, countries should take a systematic and collaborative approach in pursuing m-health policy with the focus on technological and educational support.

Development of a Maternal, Newborn and Child mHealth Intervention in Thai Nguyen Province, Vietnam: Protocol for the mMom Project

Background

Ethnic minority women (EMW) living in mountainous areas of northern Vietnam have disproportionately high infant and maternal mortality rates as a result of low maternal health knowledge, poverty, and remoteness from low-capacity health centers.

Objective

The objective of this study was to describe the protocol for the development and evaluation of the mMom intervention, which is an integrated mobile health (mHealth) system designed to improve maternal and infant health knowledge, and behavior among women in remote areas of Thai Nguyen, Vietnam.

Methods

This project featured the following four phases: (1) development of an mHealth platform integrated into the existing health management information system in partnership with the provincial health department; (2) ethnographic fieldwork and intervention content development; (3) intervention piloting and implementation; and (4) evaluation of the intervention’s impact on participants’ maternal health knowledge, behavior, and interactions with the health system.

Results

The mMom project development process resulted in the following: (1) the successful development of the mMom system, including the mHealth platform hardware and integration, the intervention plan and content, and the monitoring and evaluation framework; (2) the piloting and implementation of the intervention as planned; and (3) the implementation of the monitoring and evaluation framework components.

Conclusions

This protocol outlines the development of the mMom intervention and describes critical next steps in understanding the impact of the intervention on participants and the wider health system in Thai Nguyen province, Vietnam.

Strengthening scaling up through learning from implementation: comparing experiences from Afghanistan, Bangladesh and Uganda

Background

Many effective innovations and interventions are never effectively scaled up. Implementation research (IR) has the promise of supporting scale-up through enabling rapid learning about the intervention and its fit with the context in which it is implemented. We integrate conceptual frameworks addressing different dimensions of scaling up (specifically, the attributes of the service or innovation being scaled, the actors involved, the context, and the scale-up strategy) and questions commonly addressed by IR (concerning acceptability, appropriateness, adoption, feasibility, fidelity to original design, implementation costs, coverage and sustainability) to explore how IR can support scale-up.

Methods

We draw upon three IR studies conducted by Future Health Systems (FHS) in Afghanistan, Bangladesh and Uganda. We reviewed project documents from the period 2011–2016 to identify information related to the dimensions of scaling up. Further, for each country, we developed rich descriptions of how the research teams approached scaling up, and how IR contributed to scale-up. The rich descriptions were checked by FHS research teams. We identified common patterns and differences across the three cases.

Results

The three cases planned quite different innovations/interventions and had very different types of scale-up strategies. In all three cases, the research teams had extensive prior experience within the study communities, and little explicit attention was paid to contextual factors. All three cases involved complex interactions between the research teams and other stakeholders, among stakeholders, and between stakeholders and the intervention. The IR planned by the research teams focussed primarily on feasibility and effectiveness, but in practice, the research teams also had critical insights into other factors such as sustainability, acceptability, cost-effectiveness and appropriateness. Stakeholder analyses and other project management tools further complemented IR.

Conclusions

IR can provide significant insights into how best to scale-up a particular intervention. To take advantage of insights from IR, scale-up strategies require flexibility and IR must also be sufficiently flexible to respond to new emerging questions. While commonly used conceptual frameworks for scale-up clearly delineate actors, such as implementers, target communities and the support team, in our experience, IR blurred the links between these groups.

Electronic supplementary material

The online version of this article (doi:10.1186/s12961-017-0270-0) contains supplementary material, which is available to authorized users.

Using Theories of Change to inform implementation of health systems research and innovation: experiences of Future Health Systems consortium partners in Bangladesh, India and Uganda

Background

The Theory of Change (ToC) is a management and evaluation tool supporting critical thinking in the design, implementation and evaluation of development programmes. We document the experience of Future Health Systems (FHS) Consortium research teams in Bangladesh, India and Uganda with using ToC. We seek to understand how and why ToCs were applied and to clarify how they facilitate the implementation of iterative intervention designs and stakeholder engagement in health systems research and strengthening.

Methods

This paper combines literature on ToC, with a summary of reflections by FHS research members on the motivation, development, revision and use of the ToC, as well as on the benefits and challenges of the process. We describe three FHS teams’ experiences along four potential uses of ToCs, namely planning, communication, learning and accountability.

Results

The three teams developed ToCs for planning and evaluation purposes as required for their initial plans for FHS in 2011 and revised them half-way through the project, based on assumptions informed by and adjusted through the teams’ experiences during the previous 2 years of implementation. All teams found that the revised ToCs and their accompanying narratives recognised greater feedback among intervention components and among key stakeholders. The ToC development and revision fostered channels for both internal and external communication, among research team members and with key stakeholders, respectively. The process of revising the ToCs challenged the teams’ initial assumptions based on new evidence and experience. In contrast, the ToCs were only minimally used for accountability purposes.

Conclusions

The ToC development and revision process helped FHS research teams, and occasionally key local stakeholders, to reflect on and make their assumptions and mental models about their respective interventions explicit. Other projects using the ToC should allow time for revising and reflecting upon the ToCs, to recognise and document the adaptive nature of health systems, and to foster the time, space and flexibility that health systems strengthening programmes must have to learn from implementation and stakeholder engagement.

Electronic supplementary material

The online version of this article (doi:10.1186/s12961-017-0272-y) contains supplementary material, which is available to authorized users.

Developing mHealth Messages to Promote Postmenstrual Regulation Contraceptive Use in Bangladesh: Participatory Interview Study

BACKGROUND

Abortions are restricted in Bangladesh, but menstrual regulation is an approved alternative, defined as a procedure of regulating the menstrual cycle when menstruation is absent for a short duration. Use of contraception after menstrual regulation can reduce subsequent unintended pregnancy, but in Bangladesh, the contraceptive method mix is dominated by short-term methods, which have higher discontinuation and failure rates. Mobile phones are a channel via which menstrual regulation clients could be offered contraceptive support after leaving the clinic.

OBJECTIVE

This study aimed to support the development of a mobile phone intervention to support postmenstrual regulation family planning use in Bangladesh. It explored what family planning information women want to receive after having a menstrual regulation procedure, whether they would like to receive this information via their mobile phone, and if so, what their preferences are for the way in which it is delivered.

METHODS

We conducted participatory interviews with 24 menstrual regulation clients in Dhaka and Sylhet divisions in Bangladesh. Women were recruited from facilities in urban and peri-urban areas, which included public sector clinics supported by Ipas, an international nongovernmental organization (NGO), and NGO clinics run by Marie Stopes. Main themes covered in the interviews were factors affecting the use of contraception, what information and support women want after their menstrual regulation procedure, how respondents would prefer to receive information about contraception, and other key issues for mobile health (mHealth) interventions, such as language and privacy. As part of the in-depth interviews, women were shown and played 6 different messages about contraception on the research assistant's phone, which they were given to operate, and were then asked to give feedback.

RESULTS

Women were open to both receiving messages about family planning methods on their mobile phones and talking to a counselor about family planning methods over the phone after their menstrual regulation. Women most commonly wanted information about the contraceptive method they were currently using and wanted this information to be tailored to their particular needs. Women preferred voice messages to text and liked the interactive voice message format. When asked to repeat and identify the main points of the messages, women demonstrated good understanding of the content. Women did not seem too concerned with privacy or with others reading the messages and welcomed including their husbands in speaking to a counselor.

CONCLUSIONS

This study found that menstrual regulation clients are very interested in receiving information on their phones to support family planning use and wanted more information about the method of contraception they were using. Participatory voicemail was the preferred modality.

e-Health readiness assessment factors and measuring tools: A systematic review

BACKGROUND

The evolving, adoption and high failure nature of health information technology (HIT)/IS/T systems requires effective readiness assessment to avert increasing failures while increasing system benefits. However, literature on HIT readiness assessment is myriad and fragmented. This review bares the contours of the available literature concluding in a set of manageable and usable recommendations for policymakers, researchers, individuals and organizations intending to assess readiness for any HIT implementation.

OBJECTIVES

Identify studies, analyze readiness factors and offer recommendations.

METHOD

Published articles 1995-2016 were searched using Medline/PubMed, Cinahl, Web of Science, PsychInfo, ProQuest. Studies were included if they were assessing IS/T/mHealth readiness in the context of HIT. Articles not written in English were excluded. Themes that emerged in the process of the data synthesis were thematically analysed and interpreted.

RESULTS

Analyzed themes were found across 63 articles. In accordance with their prevalence of use, they included but not limited to "Technological readiness", 30 (46%); "Core/Need/Motivational readiness", 23 (37%); "Acceptance and use readiness", 19 (29%); "Organizational readiness", 20 (21%); "IT skills/Training/Learning readiness" (18%), "Engagement readiness", 16 (24%) and "Societal readiness" (14%). Despite their prevalence in use, "Technological readiness", "Motivational readiness" and "Engagement readiness" all had myriad and unreliable measuring tools. Core readiness had relatively reliable measuring tools, which repeatedly been used in various readiness assessment studies CONCLUSION: Thus, there is the need for reliable measuring tools for even the most commonly used readiness assessment factors/constructs: Core readiness, Engagement and buy-ins readiness, Technological readiness and IT Skills readiness as this could serve as an immediate step in conducting effective/reliable e-Health readiness assessment, which could lead to reduced HIT implementation failures.

Impact of mobile phone-based technology to improve health, population and nutrition services in Rural Bangladesh: a study protocol

Background

Mobile phone-based technology has been used in improving the delivery of healthcare services in many countries. However, data on the effects of this technology on improving primary healthcare services in resource-poor settings are limited. The aim of this study is to develop and test a mobile phone-based system to improve health, population and nutrition services in rural Bangladesh and evaluate its impact on service delivery.

Methods

The study will use a quasi-experimental pre-post design, with intervention and comparison areas. Outcome indicators will include: antenatal care (ANC), delivery care, postnatal care (PNC), neonatal care, expanded programme on immunization (EPI) coverage, and contraceptive prevalence rate (CPR). The study will be conducted over a period of 30 months, using the existing health systems of Bangladesh. The intervention will be implemented through the existing service-delivery personnel at various primary-care levels, such as community clinic, union health and family welfare centre, and upazila health complex. These healthcare providers will be given mobile phones equipped with Apps for sending text and voice messages, along with the use of Internet and device for data-capturing. Training on handling of the Smartphones, data-capturing and monitoring will be given to selected service providers. They will also be trained on inputs, editing, verifying, and monitoring the outcome variables.

Discussion

Mobile phone-based technology has the potential to improve primary healthcare services in low-income countries, like Bangladesh. It is expected that our study will contribute to testing and developing a mobile phone-based intervention to improve the coverage and quality of services. The learning can be used in other similar settings in the low-and middle-income countries.

Electronic supplementary material

The online version of this article (doi:10.1186/s12911-017-0502-9) contains supplementary material, which is available to authorized users.

An ontology of and roadmap for mHealth research

PURPOSE

Mobile health or mHealth research has been growing exponentially in recent years. However, the research on mHealth has been ad-hoc and selective without a clear definition of the mHealth domain. Without a roadmap for research we may not realize the full potential of mHealth. In this paper, we present an ontological framework to define the mHealth domain and illuminate a roadmap.

METHODS

We present an ontology of mHealth. The ontology is developed by systematically deconstructing the domain into its primary dimensions and elements. We map the extent research on mHealth in 2014 onto the ontology and highlight the bright, light, and blind/blank spots which represent the emphasis of mHealth research.

FINDINGS

The emphases of mHealth research in 2014 are very uneven. There are a few bright spots and many light spots. The research predominantly focuses on individuals' use of mobile devices and applications to capture or obtain health-related data mostly to improve quality of care through mobile intervention.

CONCLUSIONS

We argue that the emphases can be balanced in the roadmap for mHealth research. The ontological mapping plays an integral role in developing and maintaining the roadmap which can be updated periodically to continuously assess and guide mHealth research.