Int. J. Electronic Healthcare, Vol. 7, No. 4, 2014
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Role of mobile phone technology in health education in Asian and African countries: a systematic review Madhusmita Sahu Centre for Public Health Informatics, Asian Institute of Public Health, Bhubaneswar, Orissa 751002, India E-mail: [email protected]
Ashoo Grover Indian Council of Medical Research, New Delhi 110029, India E-mail: [email protected]
Ashish Joshi* Centre for Global Health and Development and Department of Health Services Research Administration, College of Public Health, University of Nebraska Medical Centre, 984385 Nebraska Medical Center, Omaha, NE 68198-4385, USA E-mail: [email protected] *Corresponding author Abstract: The objective of this systematic review was to explore the role of mobile phone technologies in delivering health education programs in Asian and African countries. The search engine used was Pubmed during 2008–2011. Randomised controlled trials or controlled studies that improved health outcomes through delivery of health educational interventions using cell phone or text messaging were included in the review. Results showed studies from six Asian and African countries including Philippines, China, Kenya, South Korea, Taiwan and India. Mobile phone technology has shown to improve health outcomes for chronic disease conditions such as diabetes, heart disease and hypertension. Additional conditions include obesity and cardiopulmonary resuscitation guidance. Other studies have shown improvement in self management of breast cancer and post-hospitalisation HIV and pharmaceutical care. Overall results of the present review showed that mobile phone technologies can be a possible solution to improve healthcare outcome. Keywords: mobile phone; health education; short message service; electronic healthcare. Reference to this paper should be made as follows: Sahu, M., Grover, A. and Joshi, A. (2014) ‘Role of mobile phone technology in health education in Asian and African countries: a systematic review’, Int. J. Electronic Healthcare, Vol. 7, No. 4, pp.269–286.
Copyright © 2014 Inderscience Enterprises Ltd.
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M. Sahu et al. Biographical notes: Madhusmita Sahu is a graduate of the PG Diploma in Public Health Informatics programme from the Centre for Public Health Informatics at Asian Institute of Public Health, Bhubaneswar (India). With a determination to be a public health educator and research analyst as her long-term career goal, she started her professional career as a Research Assistant in the Centre for Public Health Informatics. Currently, she is engaged in writing literature reviews/systematic review, field data collection/analysis, coordinating ongoing research projects including identification of the gaps and future role of mobile technologies to deliver health education in developing countries in the centre at Orissa. Ashoo Grover is a public health expert and Scientist at the Indian Council of Medical Research. She has been associated with several epidemiological and operational projects at PGIMER and has been WHO monitor for IPPI campaign and Leprosy Elimination Monitoring Exercises. She has facilitated several Government-funded training programs. At the ICMR, she is the program officer for oral health, neurological sciences and cardiovascular diseases. At the Department of Health Research of MOHFW, she is a program manager for various schemes related to human resource development and translational projects. Ashish Joshi is the Director of Population Informatics Programme and an Assistant Professor of the Center for Global Health and Development. He is a trained medical physician followed by his training in Public Health from Boston University and PhD in Health Informatics from the School of Biomedical Informatics, University of Texas Health Science Centre, Houston. His research interests include global health informatics, m-health, consumer informatics and human-centred geovisualisation. He has designed several research studies focusing on technology-enabled interventions to improve health outcomes. He has ongoing research projects in USA, India, Brazil and Nigeria.
1
Introduction
Current income growth in Asian countries is paired with a rapid demographic and epidemiologic transition (Jha and Chen, 2007). The aging population and increasing prevalence of chronic non-communicable diseases (such as heart attack, stroke, diabetes mellitus, respiratory diseases and cancer) pose a considerable challenge to the weak healthcare systems in these countries (Jha and Chen, 2007). The emerging burden of chronic diseases in South and East Asia has major health and poverty implications and present significant challenge to the governments. Majority of deaths in the age group of 30–69 years owing to chronic diseases are avoidable in Asia (Jha and Chen, 2007). These countries have recently reported an increasing incidence of chronic non-communicable diseases besides the continued existing burden of communicable diseases. More precisely, diseases formerly concentrated in developed countries, such as hypertension, obesity, heart disease and diabetes, are on the rise in these countries (Kahn et al., 2010). The combined effect of communicable and non-communicable diseases is described as a ‘dual burden’ (Boutayeb, 2006). Thus, the health status of these populations continues to be a major cause of concern. Reduction of ‘dual burden’ of diseases will improve health standards and quality of life. With every sixth human on the planet living in India,
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providing healthcare particularly to the 800 million in suburban and rural areas is a challenge (Ganapathy and Ravindra, 2008). Widespread internet access makes it a viable and logical mode of delivering health information. Mobile phone is one of the fastest growing telecommunication infrastructures at both national and global levels. Use of cell phones is as prevalent among those from a lower socioeconomic status as among those from the general population (Gitonga et al., 2010). The use of cell phones and text messaging has been found to be even higher among teens and young adults when compared with older adults (Krishna et al., 2009). The widespread distribution of cellular phones, combined with their unique ability to communicate data in real time, makes them an ideal novel healthcare delivery tool for chronic diseases (Yoo et al., 2009). Advances in the mobile health (m-health) have enabled to design, develop and evaluate new patient-centric models for the provision of tailored healthcare services, increase utilisation of patient self-management and self-control capabilities (Kouris et al., 2010). The global distribution of new, versatile, mobile technologies is wide enough that designers, developers and people with actionable ideas can use these devices to substantially transform the human experience on a global scale (Krishna et al., 2009). Mobile healthcare enables caregivers to have regular access to patients’ clinical data and latest medical knowledge (Shieh et al., 2008). It can also be utilised to improve healthcare services by improving outreach, improved communication and adherence to treatment regimen (mHealth global south landscape). Mobile health applications make communication among researchers, clinicians and patients easier (Kahn et al., 2010). Technologies such as cell phones and text messaging that are already a part of people’s daily lives have great potential for improving people’s health by assisting them with behaviour modification, health education delivery and self-management of diseases (Cole-Lewis and Kershew, 2010). Recently, a number of health and development organisations are beginning to highlight mobile technologies as a critical part of the solution to health needs including: •
educational awareness
•
remote data collection and remote monitoring
•
communication and training of healthcare workers
•
disease and epidemic outbreak tracking
•
diagnostic and treatment support.
The uses of mobile health technologies have shown to improve knowledge and health outcomes in a variety of health areas particularly in developed world (mHealth Vital wave consulting). They are aimed to improve healthcare delivery through e-care, e-services, e-surveillance and e-learning (ehealth, 2007). Some of the mobile health applications focus on increasing awareness of HIV/AIDS (Freedom HIV). The previous study has shown HIV/AIDS patients using mobile phones to access their lab tests and medical history reports, acquire nutritional planning, creating alerts to remind them to take their medications and ability to connect with a help line (Freedom HIV). Mobile handheld devices facilitate collection of health-related data and transmit it to health information database where it can be accessed on a real-time basis (mHealth development). Prior studies have also used mobile health applications to report disease incidence. Decision-makers could access and analyse this data in real time via a variety
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of tools, including geographic information systems (GIS)‐based maps (mHealth development). Voxiva has deployed a phone- and web-based data collection and disease surveillance system to quickly analyse, share information resources and adequately respond to specific health-related questions (UNPAN). Initiatives have also been taken to utilise mobile health technologies in diagnostic and in providing treatment support for various health conditions (Mobile device, 2011). Mobile health applications have also been designed to exchange patient data with doctors directly by using ‘smart’ sensors and mini-processors (Another Mobile Monitoring, 2007). At present, mobile health interventions is an emerging but a rapidly advancing field and have been conducted mostly in Japan, the USA, New Zealand and more recently, the UK. These intervention studies include diet or weight management, physical activity improvement, reduction in alcohol and drug use and smoking cessation many of which have shown positive outcomes (Blake, 2008).
2
Statement of the problem
In order for health communication system to have an impact, it should disseminate appropriate health content. In less developed countries as in Asia as well Africa, an effective health communication might be impeded by various factors, viz., low health literacy, limited internet access, lack of research activity in health education and health promotion field, low-quality healthcare information on the internet and inability of health workers to communicate with patients. Because of various communication hurdles such as language barriers and socio-cultural differences, health workers often face difficulty in transmitting important health information to their patients at a community level. Shortage of trained manpower is also a major problem particularly in developing countries. Use of mobile health technologies can improve knowledge and health outcomes in various healthcare practices; however, information is available only from the developed world. Limited studies have been performed in less developed countries where mobile health applications have been used to improve healthcare practices. Hence, the objective of our systematic review was to explore the role of mobile phone technology in the delivery of health education programmes in Asian and African countries.
3
Methodology
3.1 Source of information Information was searched using a scientific database Pubmed (http://www.ncbi.nlm. nih.gov/pubmed) during a period of 2008–2011. The following search terms were used in single or in combination: cell phone, mobile phone, text message, short message service (SMS), health education, electronic healthcare and Asian and African countries. Abstracts of the papers were reviewed and those that met the inclusion criteria were retrieved for further detailed review.
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3.2 Inclusion criteria and exclusion criteria Randomised controlled trials or controlled studies that evaluated delivery of health information or educational intervention using cell phone or text messaging and measured change in the process of care or health outcomes was included in the review process. Studies from countries other than Asia and Africa and those that were published in languages other than English were excluded.
3.3 Review process From each eligible study, data extraction was done on the following variables: the country where the study was done, study sample, mobile technology used, type of intervention, study duration and outcome measures. Additional information gathered included study design, health and conditions studied. The detailed step-by-step methodology in paper search and review process is shown in Figure 1.
3.4 Statistical analysis Univariate analysis was performed to report means and standard deviations for continuous variables and frequency statistics for categorical variables. We used T-test to compare means and standard deviations for continuous variables and Chi-square statistics to compare frequency distributions for categorical variables. The statistical software SAS V9.1 was used to perform the analysis.
4
Findings
Our initial Pubmed search yielded 622 abstracts, and after applying inclusion and exclusion criteria, only 13 papers were included in the final analysis (Figure 1). This systematic review includes intervention studies related to the use of mobile phone technology to deliver health education interventions. Results of our final analysis included studies among low-, middle- and high-income Asian and African countries (Table 1). A World Health Organization (WHO) and human development index (HDI) criterion was used to classify these countries (Ref:-Weblink-14). These countries included Philippines (n = 1), China (n = 1), Kenya (n = 1), South Korea (n = 6), Taiwan (n = 1) and India (n = 3). The duration of the studies ranged from 6 days to 12 months. Fifty seven percent (n = 8) of them had a study duration range from 6 months to 12 months and 14% (n = 2) ranged from 3 months. One of the studies had a study duration range of 4 weeks (n = 1) while other two had a study duration of 6 days (n = 2). There were two studies that did not specify the study duration. Majority of studies were performed in low-income countries (69%; n = 9/13) followed by middle income (23%; n = 3/13) and then high income (8%; n = 1/13). However, majority of the studies were conducted in countries with very HDI (62%; n = 8/13) compared with those with medium HDI (38%; n = 5/13). The average study sample size was lower in countries that had very high HDI when compared with those with a medium HDI (Mean = 114.62; SD = 118.9 vs. Mean = 192.2; SD = 205.1). However, this difference was not statistically significant (t = −0.77; p = 0.47). There was a significant difference in the average study sample size of individuals participating in
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countries in very high HDI (t = 2.73; p = 0.03) when compared with those in the medium HDI (t = 2.10; p = 0.10). Results also showed that when the average study sample size was compared based on WHO classification, the average study sample size was highest among those in the middle-income countries (Mean = 184; SD = 192) followed by low-income countries (Mean = 136; SD = 159.8) and then high-income countries (Mean = 100). There was only one country that was in the high-income category. The average study duration was higher in countries that had very high HDI when compared with those with a medium HDI (Mean = 228.5 days; SD = 126.0 vs. Mean = 190.2 days; SD = 174.18). This difference was not statistically significant (t = 0.41; p = 0.69). However, there was a significant difference in the average study duration of the individuals participating in countries in very high HDI (t = 4.44; p = 0.006) when compared with those in the medium HDI (t = 2.44; p = 0.07). Figure 1
Flow chart of the final articles included in the systematic review
Role of mobile phone technology in health education Table 1
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WHO and HDI criteria used to classify countries Human development index Study references
Study ID Countries
WHO classification
1
Philippines
Lower middle income Medium
Alis et al. (2009)
2
China
High income
Very High
Mao et al. (2008)
3
Kenya
Lower income
Medium
Lester et al. (2010)
4
Republic of Korea Low income
Very High
You et al. (2011)
5
Republic of Korea Low income
Very High
6
Taiwan
Upper middle income Very High
7
India
Low income
8
Republic of Korea Low income
Choa et al. (2008) Jen (2010)
Medium
Khokhar (2009)
Very High
Kim and Song (2008)
9
Republic of Korea Middle income
Very High
Yoo et al. (2009)
10
India
Low income
Medium
Shetty et al. (2011)
11
India
Low income
Medium
Sharma et al. (2011)
12
Republic of Korea Low income
Very High
Ahn et al. (2011)
13
Republic of Korea Low income
Very High
Yoon and Kim (2008)
Results also showed that when the average study duration was compared based on the WHO classification, the average study duration was highest among those in the low-income countries (Mean = 267; SD = 124) followed by high-income countries (Mean = 90) and then middle-income countries (Mean = 48; SD = 59.4). Results also showed that majority of the studies in the very high HDI were hospital based (75%) whereas majority of the studies in the medium HDI were community and clinic based (Figure 2). Results of the Chi-square analysis showed significant difference in the study settings and the HDI (Chi-square = 8.07; p = 0.007). Results showed that majority of the studies were hospital based in low-income countries, community based in middle-income countries and home based in high-income countries (Figure 3). However, there was only one study in the high income that was home based. Results of the Chi-square analysis showed no significant differences in the study settings and the WHO classification (Chi-square = 10.11; p = 0.12). Figure 2
Frequency of study settings stratified by HDI (see online version for colours)
276 Figure 3
M. Sahu et al. Frequency of study settings stratified by WHO classification (see online version for colours)
4.1 Study settings and disease conditions Further analysis was performed to examine various study settings where mobile health technologies have been employed (Figure 4). Majority of the studies were hospital and community based (Figure 4). Limited studies were performed in a home-based setting. Mobile health applications have shown to deliver health education for various chronic disease conditions such as diabetes and heart diseases. Other conditions for which health education was provided included oral care, obesity, diet management and cardiopulmonary resuscitation (Table 2). Advice about post-hospitalisation care, general pharmaceutical care and awareness about self-management of breast cancer was also given using mobile health technologies. Figure 4
Frequency of study settings related to mobile health interventions (see online version for colours)
Role of mobile phone technology in health education Table 2
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Diseases covered under health educational intervention studies
Diseases conditions
Intervention
Study setting
HIV/AIDS
ART and general healthcare advice Hospital based
Breast cancer
self-care awareness
Community based
General pharmaceutical care
Post-hospitalisation follow-up
Home based
Heart
Cardiological health monitoring based on ECG reading
Community based
Diabetes mellitus
Adherence to manage the diseases
Clinic based
Diabetes mellitus
Self-healthcare management
Home based
Oral care
Self-healthcare management
Home based
Maintain cardiopulmonary resuscitation Training given to the lay in case of cardiac arrest responders decay
Hospital based
CPR diseases instruction programme motion capture
School based
Healthcare education
Accurate performance of needle Healthcare education thoracocentesis in an emergency setting
Hospital based
Overweight
Self-healthcare of chronic diseases Community based
Obese with type 2 diabetes and hypertension
Self-healthcare of chronic diseases Hospital based
Obese with type 2 diabetes
Self-healthcare of chronic diseases Hospital based
The results have shown that majority of the studies were performed for diabetes (n = 4) and obesity (n = 3) followed by cardiopulmonary resuscitation training (n = 2) (Table 2).
4.2 Mobile health applications employed In majority of the studies, SMS technology was used (n = 11). Each study used video telephony technology, and voice or audiovisual animation technology. SMS technology: The outcomes of mobile-based real-time telemonitoring intervention through SMS included: •
automated classification of cardiac pathologies
•
ability to reach to underserved communities with poor or non-existent wired communication structures (Alis et al., 2009).
Mobile health applications have also been used for disease management, remote monitoring of symptoms and epidemics. Results of our review showed that majority of the studies focused on providing dietary education to prevent and manage obesity. To improve the quality and efficiency of chronic disease care, one of the studies examined the effectiveness and applicability of the ubiquitous chronic disease care (UCDC) system using cellular phones for overweight patients with both type 2 diabetes and hypertension. The UCDC system composed of a patient-based cellular phone,
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and web-based physician communication that was linked with a home blood pressure measurement and self-monitoring blood glucose system (Yoo et al., 2009). The UCDC system would send out reminder to individuals to record their blood glucose and blood pressure readings. The Anycheck device attached to their cellular phone conducted the glucose measurements and automatically sent the results to a central study database (Yoo et al., 2009). Patients immediately received messages of encouragement, reminders and recommendations according to a predefined algorithm that was developed by endocrinologists and dieticians based on the American Diabetes Association (ADA). The UCDC system automatically recorded participant’s exercise time using the SMS, which was predefined according to each patient’s daily schedule. Participants replied via an automatic answer system whether they actually exercised. Participants received information via SMS three times a day regarding healthy diet and exercise methods, along with general information about diabetes, hypertension and obesity (Yoo et al., 2009). Implementation of UCDC system resulted in significant reduction in systolic and diastolic blood pressure measurements. However, there were few limitations; •
The cost–benefit ratio of using the system in the management of chronic disease was not calculated. A study on the economic feasibility of using this healthcare delivery system is needed to determine the qualitative merits of electronic medicine.
•
The metabolic benefits of the UCDC system were examined only over a 3-month interval.
It is not clear if these effects would persist over a longer period of time (Yoo et al., 2009). In another prior study, short text messages were used to remind women to do their monthly breast self exam (BSE) to become aware of the normal look and feel of their breasts (Khokhar, 2009). The results of the study showed significant improvement in BSE practices. Furthermore, SMS was shown as a useful tool to remind individuals on an ongoing basis to self-monitor their health condition (Khokhar, 2009). Mobile health applications have also been used for the management of infectious diseases (Lester et al., 2010). In this study, mobile communication was used between healthcare workers and patients to improve adherence to antiretroviral therapy (Lester et al., 2010). Adherence is also important for programme cost containment (Bennett et al., 2008). SMS technology was also used to send reminders to diabetic patients to help them follow dietary modification, physical activity and drug schedules (Shetty et al., 2011). The study aimed to assess whether SMS via cell phones could motivate patients with diabetes to improve adherence to the treatment prescriptions and to study whether such behavioural changes could improve health outcomes. Patients found SMS as a useful tool to remind them to continue to adhere to their treatment plan and were highly accepted. The median frequency of SMS was 2 per week. Moreover, it was observed that there was a hesitancy to make clinic visits at frequent intervals. However, reminders by SMS on principles of diabetes management helped to improve the metabolic outcome among individuals (Shetty et al., 2011). Messages received through mobile phones can be stored and easily retrieved at any convenient time (Sharma et al., 2011). A recent randomised control trial was done in Karnataka, India, where education related to oral health was provided to the mothers
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of preschool children. One group of individuals received education through pamphlets while the other group received education using SMS technologies. A significant increase in knowledge, attitude and practices was recorded at the end of the trial in both the groups (Sharma et al., 2011). In another study, cardiopulmonary resuscitation training was delivered as a video on mobile phones (Kahn et al., 2010). Another study from South Korea showed individuals using mobile phones to access website that allowed them to input their blood glucose levels. Cell-phone-based personalised feedback was provided based on individual characteristics including personal and family history, smoking habits, body mass index (BMI), blood pressure and baseline laboratory data. The educational intervention using this intervention rapidly improved the glycaemic control of the patients with type 2 diabetes mellitus (Yoon and Kim, 2008). Video telephony technology: Mobile video telephony was used in a prior study to facilitate instructions for an accurate performance of needle thoracocentesis in an emergency setting (You et al., 2009). Use of an external camera in mobile phone was used to transfer the target image to the receiver on a real-time basis. Voice or audiovisual animation technology: Many mobile phones allow two-way video communication, which permits callers to hear and see each other. If used during medical emergencies, bystanders can receive supervision and guidance from medical staff based on visual information. Voice or audiovisual animation through cellular phone was found to be a potential internet-based cardiopulmonary resuscitation self-training tool for a lay person. The technology may be adapted in training remotely placed health workers and even lay individuals to manage in emergency settings. Further evaluation of this technology is warranted in different study settings.
5
Discussion
Mobile phone health technologies enable remote monitoring of patients and transform mobile phones into a viewing device through SMS and multimedia message service (MMS) (Alis et al., 2009). Results of our systematic review describe various applications where SMS technology has been used as a means of communication between healthcare provider and the patients. Mobile text message service was found both convenient and effective in health monitoring, self-management of chronic diseases, delivery of individualised pharmaceutical care, medication adherence and in public health awareness programmes such as weight control programme and breast cancer awareness (Alis et al., 2009; Jen, 2010; Khokhar, 2009; Lester et al., 2010; Mao et al., 2008). The use of MPSS might improve pharmaceutical care, widen the knowledge of pharmacists, reduce burden on pharmacy staff, improve pharmacist–patient interaction, and improve effect and safety of medications. Hence, future study should focus further evaluation of mobile-phone-based pharmaceutical care in various health problems (Mao et al., 2008). Text messaging has the potential to reach a large number of individuals at a relatively low cost and may be cost effective when compared with use of telephones (Sharma et al., 2011). A United Nations report describes mobile phones having the greatest impact in low-income
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countries (Smart Phones in Neurologic Practice). Although many low-income countries do not have widespread or even dependable broadband internet access, much of their population has access to cell phones. These devices can make it convenient to schedule appointments, receive medical results and ensure timely alerts and reminders regarding upcoming tests, procedures and medications (Vaitheeswaran, 2009). In most of the countries, patients have access to mobile technology. Use of mobile phone technologies to deliver health education is more commonly used in developed countries than others. There are only few Asian and African countries in which mobile phone technology has been reported to be used as a medium to deliver healthcare services. Furthermore, results of our review also showed that majority of the studies were hospital based and were of short duration and so it was difficult to assess the long-term impact of the interventions performed. Studies of longer duration are needed to assess the impact of mobile-based health educational interventions for the improvement of health outcomes. However, there are several limitations of the study. One of the limitations was that our search included studies that primarily evaluated mobile-based health education and so it might be that certain studies where health education was not the primary aim could have been missed. It might also be possible that some of the work may be ongoing in the area of mobile-based health education but have not yet been published in Pubmed. Another limitation of the study is generalisability of findings of our systematic review. There were very few studies that have assessed the impact of mobile-based health education on health outcomes. Only one study was done in Kenya and, therefore, the results might not be applicable to the broader populations in other settings. Similarly, there were limited studies about each health condition and the results found might not be applicable for the same disease conditions in other settings. There is a need to conduct both feasibility and intervention studies of long duration in diverse settings to assess the impact of mobile-based health educational interventions in the improvement of health outcomes. Furthermore, several barriers were identified that limited the adoption of mobile health technologies. These barriers included lack of interfaces that had good display technologies and inadequate security controls for mobile devices (Shieh et al., 2008). Other barriers include implementation of intelligent algorithms that can identify clinically significant events before notifying caregivers (Shieh et al., 2008). Accompanying them were the challenges of mindset adjustment, the empowerment of patients with medical knowledge in everyday language and ensuring the confidentiality of patient data. Social support, the help of family or friends, can also foster peer-to-peer interactions and can provide support for improved healthcare practices. More efforts should be warranted in integrating social factors along with the delivery of health education for an effective management of various disease and health issues (Kahn et al., 2010). There is a need to develop electronic healthcare standards for delivery of health educational programmes using mobile technological platforms. These standards should be applicable across various settings and facilitate a standardised approach for the design, development and evaluation of mobile-technology-enabled health education programmes. Mobile healthcare offers new opportunities for patients and healthcare professionals for a shared decision-making and facilitate delivery of tailored healthcare interventions (Shieh et al., 2008). Overall results of the present review show that mobile phone technologies can be a possible solution to improve healthcare outcomes.
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Lester, R.T., Ritvo, P., Mills, E.J., Kariri, A., Karanja, S., Chung, M.H., Jack, W, Habyarimana, J., Sadatsafavi, M., Najafzadeh, M., Marra, C.A., Estambale, B., Ngugi, E., Ball, T.B., Thabane, L., Gelmon, L.J., Kimani. J., Ackers, M. and Plummer. F.A. (2010) ‘Effects of a mobile phone short message service on antiretroviral treatment adherence in Kenya (WelTel Kenya1): a randomised trial’, Lancet, Vol. 27376, No. 9755, pp.1838–1845. Mao, Y., Zhang, Y. and Zhai, S. (2008) ‘Mobile phone text messaging for pharmaceutical care in a hospital in China’, Journal of Telemedicine and Telecare, Vol. 14, No. 8, pp.410–414. Mobile device (2011) Mobile Device will Allow Remote Health Monitoring, http://source.theengineer.co.uk/events/educational/mobile-device-will-allow-remote-healthmonitoring/391494 (Retrieved 10 February, 2011). Sharma, R., Hebbal, M., Ankola, A.V. and Murugabupathy, V. (2011) ‘Mobile-phone text messaging (SMS) for providing oral health education to mothers of preschool children in Belgaum City’, Journal of Telemedicine and Telecare, Vol. 17, No. 8, pp.432–436. Shetty, A.S., Chamukuttan, S., Nanditha, A., Raj, R.K. and Ramachandran, A. (2011) ‘Reinforcement of adherence to prescription recommendations in Asian Indian diabetes patients using short message service (SMS) – a pilot study’, The Journal of the Association of Physicians of India, Vol. 59, pp.711–714. Shieh, Y.Y., Tsai, F.Y., Anavim, A., Shieh, M., Wang, M.D. and Lin, C.M. (2008) ‘Mobile healthcare: the opportunities and challenges’, International Journal of Electronic Healthcare, Vol. 4, No. 2, pp.208–219. Vaitheeswaran, V. (2009) Medicine Goes Digital – A Special Report on Healthcare and Technology, http://fitterlife.wordpress.com/2009/04/16/medicine-goes-digital (Retrieved 16 April, 2009). Yoo, H.J., Park, M.S., Kim, T.N., Yang, S.J., Cho, G.J., Hwang, T.G., Baik, S.H., Choi, D.S., Park, G.H. and Choi, K.M. (2009) ‘A ubiquitous chronic disease care system using cellular phones and the internet’, Diabetic Medicine, Vol. 26, No. 6, pp.628–635. Yoon, K.H. and Kim, H.S. (2008) ‘A short message service by cellular phone in type 2 diabetic patients for 12 months’, Diabetes Research and Clinical Practice, Vol. 79, No. 2, pp.256–261. You, J.S., Park, S., Chung, S.P. and Park, J.W. (2009) ‘Could new communication systems be used to advise public in emergency situations? The HSDPA/WCDMA-based video telephony application to pre-hospital care medicine’, Emergency Medicine Journal, Vol. 26, No. 2, pp.152–153. You, J.S., Park, S., Chung, S.P. and Park, J.W. (2009) ‘Usefulness of a mobile phone with video telephony in identifying the correct landmark for performing needle thoracocentesis’, Emergency Medicine Journal, Vol. 26, No. 3, pp.177–179.
Websites Freedom HIV/AIDS, http://www.freedomhivaids.in/FreedomHivAids.htm mhealth for development, United Nations Public Administration Network, http://unpan1.un.org/ intradoc/groups/public/documents/unpan/unpan037268.pdf mHealth Global_South_Landscape_Analysis http://www.vitalwaveconsulting.com/pdf/mHealth _in_the_Global_South_Landscape_Analysis.pdf mHealth, http://www.vitalwaveconsulting.com/pdf/mHealth.pdf Smart Phones in Neurologic Practice, http://www.neuroguide.com/skills/smart_phones_neurologic _practice.pdf United Nations Public Administration Network (UNPAN) Mobile Application of Health and Learning, http://unpan1.un.org/intradoc/groups/public/documents/UN/UNPAN030003.pdf
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Role of mobile phone technology in health education in Asian and African countries: a systematic review Madhusmita Sahu Centre for Public Health Informatics, Asian Institute of Public Health, Bhubaneswar, Orissa 751002, India E-mail: [email protected]
Ashoo Grover Indian Council of Medical Research, New Delhi 110029, India E-mail: [email protected]
Ashish Joshi* Centre for Global Health and Development and Department of Health Services Research Administration, College of Public Health, University of Nebraska Medical Centre, 984385 Nebraska Medical Center, Omaha, NE 68198-4385, USA E-mail: [email protected] *Corresponding author Abstract: The objective of this systematic review was to explore the role of mobile phone technologies in delivering health education programs in Asian and African countries. The search engine used was Pubmed during 2008–2011. Randomised controlled trials or controlled studies that improved health outcomes through delivery of health educational interventions using cell phone or text messaging were included in the review. Results showed studies from six Asian and African countries including Philippines, China, Kenya, South Korea, Taiwan and India. Mobile phone technology has shown to improve health outcomes for chronic disease conditions such as diabetes, heart disease and hypertension. Additional conditions include obesity and cardiopulmonary resuscitation guidance. Other studies have shown improvement in self management of breast cancer and post-hospitalisation HIV and pharmaceutical care. Overall results of the present review showed that mobile phone technologies can be a possible solution to improve healthcare outcome. Keywords: mobile phone; health education; short message service; electronic healthcare. Reference to this paper should be made as follows: Sahu, M., Grover, A. and Joshi, A. (2014) ‘Role of mobile phone technology in health education in Asian and African countries: a systematic review’, Int. J. Electronic Healthcare, Vol. 7, No. 4, pp.269–286.
Copyright © 2014 Inderscience Enterprises Ltd.
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M. Sahu et al. Biographical notes: Madhusmita Sahu is a graduate of the PG Diploma in Public Health Informatics programme from the Centre for Public Health Informatics at Asian Institute of Public Health, Bhubaneswar (India). With a determination to be a public health educator and research analyst as her long-term career goal, she started her professional career as a Research Assistant in the Centre for Public Health Informatics. Currently, she is engaged in writing literature reviews/systematic review, field data collection/analysis, coordinating ongoing research projects including identification of the gaps and future role of mobile technologies to deliver health education in developing countries in the centre at Orissa. Ashoo Grover is a public health expert and Scientist at the Indian Council of Medical Research. She has been associated with several epidemiological and operational projects at PGIMER and has been WHO monitor for IPPI campaign and Leprosy Elimination Monitoring Exercises. She has facilitated several Government-funded training programs. At the ICMR, she is the program officer for oral health, neurological sciences and cardiovascular diseases. At the Department of Health Research of MOHFW, she is a program manager for various schemes related to human resource development and translational projects. Ashish Joshi is the Director of Population Informatics Programme and an Assistant Professor of the Center for Global Health and Development. He is a trained medical physician followed by his training in Public Health from Boston University and PhD in Health Informatics from the School of Biomedical Informatics, University of Texas Health Science Centre, Houston. His research interests include global health informatics, m-health, consumer informatics and human-centred geovisualisation. He has designed several research studies focusing on technology-enabled interventions to improve health outcomes. He has ongoing research projects in USA, India, Brazil and Nigeria.
1
Introduction
Current income growth in Asian countries is paired with a rapid demographic and epidemiologic transition (Jha and Chen, 2007). The aging population and increasing prevalence of chronic non-communicable diseases (such as heart attack, stroke, diabetes mellitus, respiratory diseases and cancer) pose a considerable challenge to the weak healthcare systems in these countries (Jha and Chen, 2007). The emerging burden of chronic diseases in South and East Asia has major health and poverty implications and present significant challenge to the governments. Majority of deaths in the age group of 30–69 years owing to chronic diseases are avoidable in Asia (Jha and Chen, 2007). These countries have recently reported an increasing incidence of chronic non-communicable diseases besides the continued existing burden of communicable diseases. More precisely, diseases formerly concentrated in developed countries, such as hypertension, obesity, heart disease and diabetes, are on the rise in these countries (Kahn et al., 2010). The combined effect of communicable and non-communicable diseases is described as a ‘dual burden’ (Boutayeb, 2006). Thus, the health status of these populations continues to be a major cause of concern. Reduction of ‘dual burden’ of diseases will improve health standards and quality of life. With every sixth human on the planet living in India,
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providing healthcare particularly to the 800 million in suburban and rural areas is a challenge (Ganapathy and Ravindra, 2008). Widespread internet access makes it a viable and logical mode of delivering health information. Mobile phone is one of the fastest growing telecommunication infrastructures at both national and global levels. Use of cell phones is as prevalent among those from a lower socioeconomic status as among those from the general population (Gitonga et al., 2010). The use of cell phones and text messaging has been found to be even higher among teens and young adults when compared with older adults (Krishna et al., 2009). The widespread distribution of cellular phones, combined with their unique ability to communicate data in real time, makes them an ideal novel healthcare delivery tool for chronic diseases (Yoo et al., 2009). Advances in the mobile health (m-health) have enabled to design, develop and evaluate new patient-centric models for the provision of tailored healthcare services, increase utilisation of patient self-management and self-control capabilities (Kouris et al., 2010). The global distribution of new, versatile, mobile technologies is wide enough that designers, developers and people with actionable ideas can use these devices to substantially transform the human experience on a global scale (Krishna et al., 2009). Mobile healthcare enables caregivers to have regular access to patients’ clinical data and latest medical knowledge (Shieh et al., 2008). It can also be utilised to improve healthcare services by improving outreach, improved communication and adherence to treatment regimen (mHealth global south landscape). Mobile health applications make communication among researchers, clinicians and patients easier (Kahn et al., 2010). Technologies such as cell phones and text messaging that are already a part of people’s daily lives have great potential for improving people’s health by assisting them with behaviour modification, health education delivery and self-management of diseases (Cole-Lewis and Kershew, 2010). Recently, a number of health and development organisations are beginning to highlight mobile technologies as a critical part of the solution to health needs including: •
educational awareness
•
remote data collection and remote monitoring
•
communication and training of healthcare workers
•
disease and epidemic outbreak tracking
•
diagnostic and treatment support.
The uses of mobile health technologies have shown to improve knowledge and health outcomes in a variety of health areas particularly in developed world (mHealth Vital wave consulting). They are aimed to improve healthcare delivery through e-care, e-services, e-surveillance and e-learning (ehealth, 2007). Some of the mobile health applications focus on increasing awareness of HIV/AIDS (Freedom HIV). The previous study has shown HIV/AIDS patients using mobile phones to access their lab tests and medical history reports, acquire nutritional planning, creating alerts to remind them to take their medications and ability to connect with a help line (Freedom HIV). Mobile handheld devices facilitate collection of health-related data and transmit it to health information database where it can be accessed on a real-time basis (mHealth development). Prior studies have also used mobile health applications to report disease incidence. Decision-makers could access and analyse this data in real time via a variety
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of tools, including geographic information systems (GIS)‐based maps (mHealth development). Voxiva has deployed a phone- and web-based data collection and disease surveillance system to quickly analyse, share information resources and adequately respond to specific health-related questions (UNPAN). Initiatives have also been taken to utilise mobile health technologies in diagnostic and in providing treatment support for various health conditions (Mobile device, 2011). Mobile health applications have also been designed to exchange patient data with doctors directly by using ‘smart’ sensors and mini-processors (Another Mobile Monitoring, 2007). At present, mobile health interventions is an emerging but a rapidly advancing field and have been conducted mostly in Japan, the USA, New Zealand and more recently, the UK. These intervention studies include diet or weight management, physical activity improvement, reduction in alcohol and drug use and smoking cessation many of which have shown positive outcomes (Blake, 2008).
2
Statement of the problem
In order for health communication system to have an impact, it should disseminate appropriate health content. In less developed countries as in Asia as well Africa, an effective health communication might be impeded by various factors, viz., low health literacy, limited internet access, lack of research activity in health education and health promotion field, low-quality healthcare information on the internet and inability of health workers to communicate with patients. Because of various communication hurdles such as language barriers and socio-cultural differences, health workers often face difficulty in transmitting important health information to their patients at a community level. Shortage of trained manpower is also a major problem particularly in developing countries. Use of mobile health technologies can improve knowledge and health outcomes in various healthcare practices; however, information is available only from the developed world. Limited studies have been performed in less developed countries where mobile health applications have been used to improve healthcare practices. Hence, the objective of our systematic review was to explore the role of mobile phone technology in the delivery of health education programmes in Asian and African countries.
3
Methodology
3.1 Source of information Information was searched using a scientific database Pubmed (http://www.ncbi.nlm. nih.gov/pubmed) during a period of 2008–2011. The following search terms were used in single or in combination: cell phone, mobile phone, text message, short message service (SMS), health education, electronic healthcare and Asian and African countries. Abstracts of the papers were reviewed and those that met the inclusion criteria were retrieved for further detailed review.
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3.2 Inclusion criteria and exclusion criteria Randomised controlled trials or controlled studies that evaluated delivery of health information or educational intervention using cell phone or text messaging and measured change in the process of care or health outcomes was included in the review process. Studies from countries other than Asia and Africa and those that were published in languages other than English were excluded.
3.3 Review process From each eligible study, data extraction was done on the following variables: the country where the study was done, study sample, mobile technology used, type of intervention, study duration and outcome measures. Additional information gathered included study design, health and conditions studied. The detailed step-by-step methodology in paper search and review process is shown in Figure 1.
3.4 Statistical analysis Univariate analysis was performed to report means and standard deviations for continuous variables and frequency statistics for categorical variables. We used T-test to compare means and standard deviations for continuous variables and Chi-square statistics to compare frequency distributions for categorical variables. The statistical software SAS V9.1 was used to perform the analysis.
4
Findings
Our initial Pubmed search yielded 622 abstracts, and after applying inclusion and exclusion criteria, only 13 papers were included in the final analysis (Figure 1). This systematic review includes intervention studies related to the use of mobile phone technology to deliver health education interventions. Results of our final analysis included studies among low-, middle- and high-income Asian and African countries (Table 1). A World Health Organization (WHO) and human development index (HDI) criterion was used to classify these countries (Ref:-Weblink-14). These countries included Philippines (n = 1), China (n = 1), Kenya (n = 1), South Korea (n = 6), Taiwan (n = 1) and India (n = 3). The duration of the studies ranged from 6 days to 12 months. Fifty seven percent (n = 8) of them had a study duration range from 6 months to 12 months and 14% (n = 2) ranged from 3 months. One of the studies had a study duration range of 4 weeks (n = 1) while other two had a study duration of 6 days (n = 2). There were two studies that did not specify the study duration. Majority of studies were performed in low-income countries (69%; n = 9/13) followed by middle income (23%; n = 3/13) and then high income (8%; n = 1/13). However, majority of the studies were conducted in countries with very HDI (62%; n = 8/13) compared with those with medium HDI (38%; n = 5/13). The average study sample size was lower in countries that had very high HDI when compared with those with a medium HDI (Mean = 114.62; SD = 118.9 vs. Mean = 192.2; SD = 205.1). However, this difference was not statistically significant (t = −0.77; p = 0.47). There was a significant difference in the average study sample size of individuals participating in
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countries in very high HDI (t = 2.73; p = 0.03) when compared with those in the medium HDI (t = 2.10; p = 0.10). Results also showed that when the average study sample size was compared based on WHO classification, the average study sample size was highest among those in the middle-income countries (Mean = 184; SD = 192) followed by low-income countries (Mean = 136; SD = 159.8) and then high-income countries (Mean = 100). There was only one country that was in the high-income category. The average study duration was higher in countries that had very high HDI when compared with those with a medium HDI (Mean = 228.5 days; SD = 126.0 vs. Mean = 190.2 days; SD = 174.18). This difference was not statistically significant (t = 0.41; p = 0.69). However, there was a significant difference in the average study duration of the individuals participating in countries in very high HDI (t = 4.44; p = 0.006) when compared with those in the medium HDI (t = 2.44; p = 0.07). Figure 1
Flow chart of the final articles included in the systematic review
Role of mobile phone technology in health education Table 1
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WHO and HDI criteria used to classify countries Human development index Study references
Study ID Countries
WHO classification
1
Philippines
Lower middle income Medium
Alis et al. (2009)
2
China
High income
Very High
Mao et al. (2008)
3
Kenya
Lower income
Medium
Lester et al. (2010)
4
Republic of Korea Low income
Very High
You et al. (2011)
5
Republic of Korea Low income
Very High
6
Taiwan
Upper middle income Very High
7
India
Low income
8
Republic of Korea Low income
Choa et al. (2008) Jen (2010)
Medium
Khokhar (2009)
Very High
Kim and Song (2008)
9
Republic of Korea Middle income
Very High
Yoo et al. (2009)
10
India
Low income
Medium
Shetty et al. (2011)
11
India
Low income
Medium
Sharma et al. (2011)
12
Republic of Korea Low income
Very High
Ahn et al. (2011)
13
Republic of Korea Low income
Very High
Yoon and Kim (2008)
Results also showed that when the average study duration was compared based on the WHO classification, the average study duration was highest among those in the low-income countries (Mean = 267; SD = 124) followed by high-income countries (Mean = 90) and then middle-income countries (Mean = 48; SD = 59.4). Results also showed that majority of the studies in the very high HDI were hospital based (75%) whereas majority of the studies in the medium HDI were community and clinic based (Figure 2). Results of the Chi-square analysis showed significant difference in the study settings and the HDI (Chi-square = 8.07; p = 0.007). Results showed that majority of the studies were hospital based in low-income countries, community based in middle-income countries and home based in high-income countries (Figure 3). However, there was only one study in the high income that was home based. Results of the Chi-square analysis showed no significant differences in the study settings and the WHO classification (Chi-square = 10.11; p = 0.12). Figure 2
Frequency of study settings stratified by HDI (see online version for colours)
276 Figure 3
M. Sahu et al. Frequency of study settings stratified by WHO classification (see online version for colours)
4.1 Study settings and disease conditions Further analysis was performed to examine various study settings where mobile health technologies have been employed (Figure 4). Majority of the studies were hospital and community based (Figure 4). Limited studies were performed in a home-based setting. Mobile health applications have shown to deliver health education for various chronic disease conditions such as diabetes and heart diseases. Other conditions for which health education was provided included oral care, obesity, diet management and cardiopulmonary resuscitation (Table 2). Advice about post-hospitalisation care, general pharmaceutical care and awareness about self-management of breast cancer was also given using mobile health technologies. Figure 4
Frequency of study settings related to mobile health interventions (see online version for colours)
Role of mobile phone technology in health education Table 2
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Diseases covered under health educational intervention studies
Diseases conditions
Intervention
Study setting
HIV/AIDS
ART and general healthcare advice Hospital based
Breast cancer
self-care awareness
Community based
General pharmaceutical care
Post-hospitalisation follow-up
Home based
Heart
Cardiological health monitoring based on ECG reading
Community based
Diabetes mellitus
Adherence to manage the diseases
Clinic based
Diabetes mellitus
Self-healthcare management
Home based
Oral care
Self-healthcare management
Home based
Maintain cardiopulmonary resuscitation Training given to the lay in case of cardiac arrest responders decay
Hospital based
CPR diseases instruction programme motion capture
School based
Healthcare education
Accurate performance of needle Healthcare education thoracocentesis in an emergency setting
Hospital based
Overweight
Self-healthcare of chronic diseases Community based
Obese with type 2 diabetes and hypertension
Self-healthcare of chronic diseases Hospital based
Obese with type 2 diabetes
Self-healthcare of chronic diseases Hospital based
The results have shown that majority of the studies were performed for diabetes (n = 4) and obesity (n = 3) followed by cardiopulmonary resuscitation training (n = 2) (Table 2).
4.2 Mobile health applications employed In majority of the studies, SMS technology was used (n = 11). Each study used video telephony technology, and voice or audiovisual animation technology. SMS technology: The outcomes of mobile-based real-time telemonitoring intervention through SMS included: •
automated classification of cardiac pathologies
•
ability to reach to underserved communities with poor or non-existent wired communication structures (Alis et al., 2009).
Mobile health applications have also been used for disease management, remote monitoring of symptoms and epidemics. Results of our review showed that majority of the studies focused on providing dietary education to prevent and manage obesity. To improve the quality and efficiency of chronic disease care, one of the studies examined the effectiveness and applicability of the ubiquitous chronic disease care (UCDC) system using cellular phones for overweight patients with both type 2 diabetes and hypertension. The UCDC system composed of a patient-based cellular phone,
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and web-based physician communication that was linked with a home blood pressure measurement and self-monitoring blood glucose system (Yoo et al., 2009). The UCDC system would send out reminder to individuals to record their blood glucose and blood pressure readings. The Anycheck device attached to their cellular phone conducted the glucose measurements and automatically sent the results to a central study database (Yoo et al., 2009). Patients immediately received messages of encouragement, reminders and recommendations according to a predefined algorithm that was developed by endocrinologists and dieticians based on the American Diabetes Association (ADA). The UCDC system automatically recorded participant’s exercise time using the SMS, which was predefined according to each patient’s daily schedule. Participants replied via an automatic answer system whether they actually exercised. Participants received information via SMS three times a day regarding healthy diet and exercise methods, along with general information about diabetes, hypertension and obesity (Yoo et al., 2009). Implementation of UCDC system resulted in significant reduction in systolic and diastolic blood pressure measurements. However, there were few limitations; •
The cost–benefit ratio of using the system in the management of chronic disease was not calculated. A study on the economic feasibility of using this healthcare delivery system is needed to determine the qualitative merits of electronic medicine.
•
The metabolic benefits of the UCDC system were examined only over a 3-month interval.
It is not clear if these effects would persist over a longer period of time (Yoo et al., 2009). In another prior study, short text messages were used to remind women to do their monthly breast self exam (BSE) to become aware of the normal look and feel of their breasts (Khokhar, 2009). The results of the study showed significant improvement in BSE practices. Furthermore, SMS was shown as a useful tool to remind individuals on an ongoing basis to self-monitor their health condition (Khokhar, 2009). Mobile health applications have also been used for the management of infectious diseases (Lester et al., 2010). In this study, mobile communication was used between healthcare workers and patients to improve adherence to antiretroviral therapy (Lester et al., 2010). Adherence is also important for programme cost containment (Bennett et al., 2008). SMS technology was also used to send reminders to diabetic patients to help them follow dietary modification, physical activity and drug schedules (Shetty et al., 2011). The study aimed to assess whether SMS via cell phones could motivate patients with diabetes to improve adherence to the treatment prescriptions and to study whether such behavioural changes could improve health outcomes. Patients found SMS as a useful tool to remind them to continue to adhere to their treatment plan and were highly accepted. The median frequency of SMS was 2 per week. Moreover, it was observed that there was a hesitancy to make clinic visits at frequent intervals. However, reminders by SMS on principles of diabetes management helped to improve the metabolic outcome among individuals (Shetty et al., 2011). Messages received through mobile phones can be stored and easily retrieved at any convenient time (Sharma et al., 2011). A recent randomised control trial was done in Karnataka, India, where education related to oral health was provided to the mothers
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of preschool children. One group of individuals received education through pamphlets while the other group received education using SMS technologies. A significant increase in knowledge, attitude and practices was recorded at the end of the trial in both the groups (Sharma et al., 2011). In another study, cardiopulmonary resuscitation training was delivered as a video on mobile phones (Kahn et al., 2010). Another study from South Korea showed individuals using mobile phones to access website that allowed them to input their blood glucose levels. Cell-phone-based personalised feedback was provided based on individual characteristics including personal and family history, smoking habits, body mass index (BMI), blood pressure and baseline laboratory data. The educational intervention using this intervention rapidly improved the glycaemic control of the patients with type 2 diabetes mellitus (Yoon and Kim, 2008). Video telephony technology: Mobile video telephony was used in a prior study to facilitate instructions for an accurate performance of needle thoracocentesis in an emergency setting (You et al., 2009). Use of an external camera in mobile phone was used to transfer the target image to the receiver on a real-time basis. Voice or audiovisual animation technology: Many mobile phones allow two-way video communication, which permits callers to hear and see each other. If used during medical emergencies, bystanders can receive supervision and guidance from medical staff based on visual information. Voice or audiovisual animation through cellular phone was found to be a potential internet-based cardiopulmonary resuscitation self-training tool for a lay person. The technology may be adapted in training remotely placed health workers and even lay individuals to manage in emergency settings. Further evaluation of this technology is warranted in different study settings.
5
Discussion
Mobile phone health technologies enable remote monitoring of patients and transform mobile phones into a viewing device through SMS and multimedia message service (MMS) (Alis et al., 2009). Results of our systematic review describe various applications where SMS technology has been used as a means of communication between healthcare provider and the patients. Mobile text message service was found both convenient and effective in health monitoring, self-management of chronic diseases, delivery of individualised pharmaceutical care, medication adherence and in public health awareness programmes such as weight control programme and breast cancer awareness (Alis et al., 2009; Jen, 2010; Khokhar, 2009; Lester et al., 2010; Mao et al., 2008). The use of MPSS might improve pharmaceutical care, widen the knowledge of pharmacists, reduce burden on pharmacy staff, improve pharmacist–patient interaction, and improve effect and safety of medications. Hence, future study should focus further evaluation of mobile-phone-based pharmaceutical care in various health problems (Mao et al., 2008). Text messaging has the potential to reach a large number of individuals at a relatively low cost and may be cost effective when compared with use of telephones (Sharma et al., 2011). A United Nations report describes mobile phones having the greatest impact in low-income
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countries (Smart Phones in Neurologic Practice). Although many low-income countries do not have widespread or even dependable broadband internet access, much of their population has access to cell phones. These devices can make it convenient to schedule appointments, receive medical results and ensure timely alerts and reminders regarding upcoming tests, procedures and medications (Vaitheeswaran, 2009). In most of the countries, patients have access to mobile technology. Use of mobile phone technologies to deliver health education is more commonly used in developed countries than others. There are only few Asian and African countries in which mobile phone technology has been reported to be used as a medium to deliver healthcare services. Furthermore, results of our review also showed that majority of the studies were hospital based and were of short duration and so it was difficult to assess the long-term impact of the interventions performed. Studies of longer duration are needed to assess the impact of mobile-based health educational interventions for the improvement of health outcomes. However, there are several limitations of the study. One of the limitations was that our search included studies that primarily evaluated mobile-based health education and so it might be that certain studies where health education was not the primary aim could have been missed. It might also be possible that some of the work may be ongoing in the area of mobile-based health education but have not yet been published in Pubmed. Another limitation of the study is generalisability of findings of our systematic review. There were very few studies that have assessed the impact of mobile-based health education on health outcomes. Only one study was done in Kenya and, therefore, the results might not be applicable to the broader populations in other settings. Similarly, there were limited studies about each health condition and the results found might not be applicable for the same disease conditions in other settings. There is a need to conduct both feasibility and intervention studies of long duration in diverse settings to assess the impact of mobile-based health educational interventions in the improvement of health outcomes. Furthermore, several barriers were identified that limited the adoption of mobile health technologies. These barriers included lack of interfaces that had good display technologies and inadequate security controls for mobile devices (Shieh et al., 2008). Other barriers include implementation of intelligent algorithms that can identify clinically significant events before notifying caregivers (Shieh et al., 2008). Accompanying them were the challenges of mindset adjustment, the empowerment of patients with medical knowledge in everyday language and ensuring the confidentiality of patient data. Social support, the help of family or friends, can also foster peer-to-peer interactions and can provide support for improved healthcare practices. More efforts should be warranted in integrating social factors along with the delivery of health education for an effective management of various disease and health issues (Kahn et al., 2010). There is a need to develop electronic healthcare standards for delivery of health educational programmes using mobile technological platforms. These standards should be applicable across various settings and facilitate a standardised approach for the design, development and evaluation of mobile-technology-enabled health education programmes. Mobile healthcare offers new opportunities for patients and healthcare professionals for a shared decision-making and facilitate delivery of tailored healthcare interventions (Shieh et al., 2008). Overall results of the present review show that mobile phone technologies can be a possible solution to improve healthcare outcomes.
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![[Health education through a pediatric mobile phone application].](/assets/img/hold.png)
