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

Khatun, Fatema; Heywood, Anita E.; Ray, Pradeep; Hanifi, Syed Manzoor Ahmed; Bhuiya, Abbas; Liaw, Siaw‐Teng

doi:10.1016/j.ijmedinf.2015.06.008

Cited by 95 publications

(87 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In a rural community of Bangladesh, Khatun, et al surveyed 4,915 randomly selected household members aged 18 years and older [10]. The research team found only 5% of participants had internet connectivity, only 50% were aware of short message service applications, and only 37% generally read them.…”

Section: A Framework For Readinessmentioning

confidence: 99%

See 1 more Smart Citation

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

Weichelt¹,

Bendixsen²,

Patrick³

2018

Preprint

View full text Add to dashboard Cite

show abstract

Section: A Framework For Readinessmentioning

confidence: 99%

“…The existing theme categories, identified by Khatun, et al in their study of barriers to rural community readiness to adopt mHealth [10], were used as a starting point. Those categories were technological readiness, motivational readiness, and human resource readiness.…”

Section: Coding: Identifying Themes and Categoriesmentioning

confidence: 99%

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

Weichelt¹,

Bendixsen²,

Patrick³

2018

Preprint

View full text Add to dashboard Cite

show abstract

“…For instance, [39] and [40] warned for the potential harm associated with unsafe social media content, as people seeking health information has to recognize that the authorship is difficult to determine, sources are rarely provided, and users may post their personal opinions in social marketing [41] and cause concerns of inequalities [42], privacy, misinformation and lack of evaluation [43]. For instance, there is a scandal involved China's top internet search engine, Baidu, of which the company's search engine provides medical information based on bidding process that caused the death of a university student [44].…”

Section: Potentials Of Social Media In Health Communicationmentioning

confidence: 99%

The Emerging Web 2.0 Social Media as a Tool to Develop Engaged Audiences for Behaviour Change in Health Promotion: An Overview

AuYong

Yeoh

2017

SHS Web Conf.

View full text Add to dashboard Cite

Abstract. Sharing of health information which is related to health becomes easier with the introduction of new technologies such as Web 2.0 social media networks. Social media networks represent a rather innovative way of online information and knowledge repositories. On the other hand, many non-communicable diseases are caused by unhealthy urban lifestyle. Hence, the practice of the healthy lifestyle behaviors should be promoted for sustainability. Besides, in order to cut down the chronic diseases, workplace is one of the key channels for the delivery of interventions among adult populations. Latest development in information and communication technologies (ICT) has given positive influences in health communication. The new technology is believed to be more engaged because it involves visual, audio and animation simultaneously, thus it is more reachable and collaborative. This paper reviews strategies to manage health promotion. Nevertheless, improvement is still needed to achieve successful health promotion. This paper also provides insights of issues and poses future topics of health promotion to consider.

show abstract

“…Few researchers have applied quantitative analysis to the study of mobile health care adoption. Akter et al [28][29][30][31][32][33][34][35] have tested estimated stratification using a partial least squares (PLS) path model. They demonstrated that reliability has both direct and indirect influence on sustaining the utilization of mobile health care information services.…”

Section: Foreign and Domestic Studiesmentioning

confidence: 99%

Key Influence Factors of Consumers� Intentions Towards Mobile Health Care Promotion: An Empirical Study Based on the DDANPMV Model

Liu¹,

Yang²,

Liu³

et al. 2017

Preprint

View full text Add to dashboard Cite

IntroductionMobile health care is an important aspect of electronic medicine that involves using mobile devices (e.g., mobile phones, tablet computers, and personal digital assistants) to provide medical services and health information to patients [1]. Health care faces numerous problems, including high medical costs, restricted coverage, complex medical procedures, and uneven distribution of resources [2]. Mobile health care can help to reduce medical costs and waiting times and improve the efficiency of medical resources use [3]. Mobile health care involves the following categories [4]: (1) Mobile phone applications such as Chun Yu Yi Sheng, which acts as an information exchange platform linking doctors and patients, and comprehensive mobile health care platforms that hospital service providers can apply for appointment registrations, payments, and medical alerts. (2) The collection of users' medical data through wearable devices or mobile intelligent terminals for health monitoring. For example, Kangkang launched a portable intelligent sphygmomanometer that can dynamically monitor blood pressure over a 24-hour period and automatically send data to a corresponding server. Users can view their 24-hour blood pressure analysis report through WeChat. (3) Diagnosis systems that connect with the Internet of Things (IoT). For example, an integrated diagnosis system developed by German researchers can transmit medical data to smart phones through Bluetooth technology. Smartphones applications can then process these data for reference and diagnosis.With the development of mobile networks, many countries have entered the 4G era and benefit from continuously improving mobile communication networks and innovation in software and hardware technology. Abstract: Identifying the key influence factors of mobile health care adoption is a key issue. We established an evaluation index system for consumer adoption and verified the effectiveness of our model by using a DDANPMV model. This model comprises three parts: (1) the decision making trial and evaluation laboratory (DEMATEL) technique, which is used to establish an influence network relationship map at both the "dimensions" and "criteria" levels; (2) a DEMATEL-based analytic network process (ANP; DANP), which determines the interrelationships and influential weights among the criteria; and (3) a modified VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, which applies the influence weights obtained through DANP to performance gaps regarding consumer perception. VIKOR thereby evaluates and improves performance gaps with the aims of satisfying consumer needs, achieving continuous improvement, and enabling sustainable product development. The main innovation of this method is the construction of the DDANPMV model, which integrates the DEMATEL, DANP, and modified VIKOR approaches 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 b...

show abstract

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

Cited by 95 publications

References 43 publications

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

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

The Emerging Web 2.0 Social Media as a Tool to Develop Engaged Audiences for Behaviour Change in Health Promotion: An Overview

Key Influence Factors of Consumers� Intentions Towards Mobile Health Care Promotion: An Empirical Study Based on the DDANPMV Model

Contact Info

Product

Resources

About