The combined searches from PubMed (576), Scopus (326) and hand searches (40) returned 942 resources, of which 54 studies met the study inclusion and exclusion criteria (Figure 1).
Research methods used in the 54 reviewed resources were: 25 qualitative papers [17-41], 9 surveys [42-50], 7 mixed methods [51-57], 4 experimental [52, 58-60], 3 usability assessments [8, 61, 62], 2 cohort studies [63, 64], and 4 cross sectional studies [65-68]. Collectively they reported the spectrum of factors that affect patient adoption. The papers reported a variety of m-health uses, including assisting communication and information management [18, 22, 24, 28, 31, 33, 40, 54, 61], HIV/AIDs and tuberculosis drug adherence [21, 26, 27, 38, 39, 44, 45, 48, 50-52, 57-60, 67-69], maternal health support [8, 19, 21, 25, 27, 29, 41, 49, 50, 62], mental health support [35, 43, 55, 64], and monitoring malaria [47, 65]. Data were abstracted and adoption factors initially summarised and grouped under headings based on 11 common uses of m-Health extracted from the results. These data were then separated into specific factors that promoted or impeded patient m-health adoption in the developing world and initially categorised under 22 thematic headings. Continued iterative review reduced these to seven primary categories, with 21 sub-categories (Table 1). Exactly why an element was placed in one category versus another will inevitably involve some subjectivity. For example, language can be ‘personal’ (a user characteristic) or ‘contextual’ (a population characteristic and deserving of distinct identification). Similarly, ‘cost’ is something an individual incurs (and influences ownership), whereas ‘funding’ is typically provided by institutions and not individuals (often associated with ‘collaboration’). Judging from the frequency with which an issue was addressed, the most influential factors were cost and ownership and user characteristics, with the remainder notably less (but each similarly) influential. These are described below.
Cost and ownership
Cost and ownership issues related to the impact of ownership of a mobile device, and included access to mobile devices and their affordability in terms of fixed (purchase) and variable (use) costs to patients. These issues were collated into four subcategories. Some issues were related to cost, affordability, and incentives. When the operating costs are not affordable [17, 18, 43, 44, 51, 60, 61], and patients must buy airtime (i.e., where the patient pays for the calls or messages he/she receives or makes in accessing m-healthcare from the service provider [63]), m-health is likely to fail, unless the patient is able or willing to pay [19, 45]. Patients may accept the technology if the cost of owning and operating it is considered acceptable [29, 45]. Such challenges can be reduced by introducing financial incentives to mitigate the cost burden on the patient [74]. Overall there was a lack of evidence of the cost-benefit of m-health systems which also challenges their implementation.
Other issues related to actual cell phone ownership, which was identified as a critical determinant in the adoption and uptake of m-health services [44, 46, 63], included owning the appropriate mobile phone with the required technology [47, 58, 65]. One study noted that globally, women are 21% less likely to own a mobile phone than men [25]. It was noted that ownership also influenced behaviour, with patients who received m-health services on their own phones considering it more acceptable, compared to those who shared the phone with others [20, 21, 75].
Another issue was the ability to keep a mobile phone charged and connected, and the associated costs. In many developing countries power was described as irregular with rural areas being most affected [53, 70]. Keeping a mobile phone charged was problematic [33, 36, 43] and it was common to find people paying to charge their phones at street side vendors [33, 37]. Likewise, phone maintenance in the event of a fault was an equally important factor that might jeopardise adoption [50, 53, 76].
Sharing of mobile devices was the primary issue identified under access to mobile devices. Many projects relied upon shared use of cell phones [19, 48, 77]. Although the absolute proportion of shared devices varied, for example from 21% [25] to 51.4% [8], it was recognised as a limitation to implementation. Related to cost and ownership was user characteristic issues, described below.
User characteristics
This category was also commonly reported and addressed the socio-cultural beliefs, perceptions, and overall setting of patients as factors that impact m-health adoption. The four sub-categories included the impact of socio-cultural practices and beliefs, and gender issues which were noted in many studies. Information and communications technology use in low-income countries is lower among females [44, 78, 79] and a ‘gatekeeper effect’ was noted in several studies with women requiring permission from their parents, husband or partner to use a cellphone [25, 30, 42]. This was exacerbated by being ashamed to raise issues about women’s diseases with their gatekeeper [42] or fear of punishment if they accessed a phone without permission [37]. Other cultural factors impacted cellphone use, with boys - unlike girls - being allowed to be inquisitive and seek out information about sexual matters [30], and restricted use being enforced through fear of “inappropriate” calling with the opposite sex [37]. In Tanzania, men prevented their wives from owning mobile phones because they believed it facilitated sexual unfaithfulness [62].
Studies reported participants from adolescents to the aged, of both genders, and broad levels of education [21, 28, 37, 53, 66]. Some studies suggested that age and gender of patients should be considered when implementing m-health systems, with different age groups having preferences for certain multimedia elements [48, 66], and women given less priority in male dominated communities [37, 42]. Others reported that children, the elderly and the illiterate needed assistance to initiate a service request [28], or appropriate training for them to use the device [80]. Others found all age groups, genders, and education levels functioned well with m-health interventions [8, 21].
Men dominated mobile phone use [21, 33, 44, 66, 79, 81], although this varied by country [37, 42]. Reasons included the gatekeeper effect, but also the lack of primary or higher education for women [8, 33]. It was suggested that an appropriate age target for minimally educated women to use m-health would be 17 to 63 years [8, 22, 25] but in certain parts of the developing world older women were more likely to own and use a mobile phone for m-health than younger women [53], and in South Africa women are the dominant users [37]. Urban women found evening m-health services more convenient and rural women preferred daytime services [19, 28, 57].
Acceptability and perception of use, and the willingness and ability of patients to use m-Health were identified as issues impacting implementation. m-health solutions were more readily accepted and adopted by patients when they addressed a patient recognised health need [24, 42, 43], were considered acceptable and useful to them [18, 21, 27, 45], were friendly and easy to use [26, 27, 50], and used appropriate multimedia modes (selected for effective communication by the target user group, whether text message, audio, video, animation, or pictures [65]. It was noted that audio (voice) accommodated those with low literacy and helped to build trust [19, 43, 59], while SMS messaging accommodated those with a slightly higher level of literacy [20, 21, 59, 69]. Services that did not address patients’ perceived needs impacted motivation to use the service [42].
The competence and readiness of healthcare workers to use technology to deliver an m-health solution also impacted patient adoption. Patients expected healthcare workers to respond to any requests in a timely manner [42, 77], and to have the requisite competencies to deliver the m-health services [33], highlighting the need for available and efficient training in the use and management of any m-health technology [52].
Language and Literacy
These were considered primary issues for successful m-health adoption [66, 67, 69]. The clinical benefits of conversing with a patient in their mother tongue, whether written or spoken were noted [82, 83] and m-health adoption was affected when patients were not confident in communicating in a language they did not normally use or understand [22, 61]. It was suggested that the National official language, which generally serves the interest of the majority, should be used in the deployment of m-health systems [46].
To participate in m-health services, patients need to be literate both in the traditional sense (able to read, write, and speak in their mother language), but also in a broader sense (able to understand the technical needs to effectively use a mobile device, and able to understand their health issues and treatment) [24, 46]. In poor rural areas where education levels are often lower [42] people may require the assistance of a family or community member to understand the content of a message sent to them [56]. In general m-health requires minimum literacy on the part of patients for its adoption [65], particularly when patients are appropriately trained to apply the technology [8, 24-26, 48, 49, 66].
Infrastructure
The lack of, or insufficient accessibility to, digital infrastructure in the developing world was noted [1, 30]. Unreliable or poor quality infrastructure [1, 19, 30, 40, 64, 65] leading to mobile network fluctuations [8] or inadequate cellular signal [29], and unresolved technical issues [67] were identified impediments to m-health adoption. Technology infrastructure upgrade may be required before m-health implementation to provide dependable network infrastructure, remote accessibility, and seamless connectivity [18, 28, 31, 49, 50]. In addition, m-Health interventions are dependent upon reliable electric power [28], although alternate innovative means such as ‘pedal power’ and solar power have been used to a modest degree [84, 85].
Social networks highlighting m-health services provided effective publicity and promoted implementation [53].
Collaboration and Funding
m-Health system implementation and patient adoption often relies on the fusion of various independent systems and strong stakeholder collaboration [21, 77]. Relevant stakeholder institutions must be willing to actively collaborate and share resources for success. This requires and an appropriate institutional setting that promotes such integration [44], where existing communities, healthcare facilities, technology infrastructure, and other service provider platforms are linked to each other in a seamless connectivity [8, 21, 70]. Collaboration is also necessary to identify and address patients’ challenges during implementation [70]. Very clear stakeholder responsibilities are required to avoid conflict and service ambiguity. The required level of integration can be made possible when there is an existing institutional framework supporting the exchange backed by a comprehensive policy regime. The need to engage policy makers even at the stage of design through to implementation and ensuring that the system does not run in isolation to similar national or local interventions is critical to adoption.
As the government of most countries is either the sole or primary provider – or payer – of healthcare services, government facilitation and sponsorship of m-health implementations will influence adoption by patients. Government or private sponsorship (or perception of the same) is crucial for m-health adoption among patients [45]. For some patients, just involvement of government is enough to give the project some credibility.
Community ownership of m-health programmes affects patient adoption. Mbuagbaw et al. [52] found that strong community involvement driven by advocacy during home and hospital visits, coupled with active engagement with community leaders, was an important element for patients’ adoption. Advocacy both at the level of the community and the healthcare provider is crucial for the undecided user to make up her mind [32]. This system should be implemented to reflect the local contexts in which it is deployed. There must be an effort at mobilising resources from the community to support the project internally rather than a concentration on external funding sources, if the project must succeed [52]. There must be a fusion between the community and the facility-based services for the system to reflect community context and ownership [21, 24].
The success of m-health systems depends on securing sustainable funding. Some of this funding will come from external sources and as such may not be reliable. For sustainability there should be mobilisation of community resources as well funding from external (government) sources, and an avoidance of over reliance on less secure external funding [52] (e.g., faith-based organisations and other non-governmental organisations).
There is a high probability of m-health adoption when there is collaboration among relevant governmental and non-governmental agencies, local community organisations, and funding agencies to reduce cost and promote system ownership [54].
Governance
Governance encompasses all of the processes that wield influence over a social system (country, organisation, village, tribe) through tools such as laws, regulations, or social norms. The patient-related m-health adoption governance issues include legal, regulatory, and ethical issues including data security aspects to maintain the privacy and confidentiality of healthcare information, records and communications [70, 86]. Each of these were noted to impact patient adoption of m-health [21, 45, 59, 67].
An enabling regulatory setting requires suitable laws, policies, and a framework that supports m-health adoption by patients. Legal and regulatory challenges to successful m-health adoption were noted [70], requiring appropriate responses using policies, standards, and regulations [86]. The implementation of a regulatory policy must be the responsibility of all stakeholders especially the regulator and the healthcare provider [70].
Maintaining the privacy of data during collection, storage, and sharing for all patient groups was noted as critical for the adoption and sustainability of m-health systems [20, 51, 59, 63, 67, 76]. Success instilled confidence in patients [17, 27, 63, 87] while failure had a negative impact [52]. Protecting m-health devices against unauthorised access and having effective standard operating procedures was also noted [28].
Some patients wanted all communications sent directly to their personal mobile devices without going through a human intermediary to guarantee confidentiality [62]. Yet where a patient does not own a mobile phone, caregivers must be contacted to make the information available to the patient; some considered this a breach of confidentiality [57, 73], because mobile phone is considered a preferred medium for communicating sensitive issues [72]. Confidentiality concerns were even noted regarding asking for socio-demographic information from patients [45].
System Utility
The final category refers to how useful or beneficial an m-health solution is to patients. Three sub-categories were identified: Demonstrating clear benefit to patients, the effectiveness of the system, and evaluation and monitoring.
m-Health systems were found to be more readily adopted when they demonstrated clear benefits to patients [32, 52, 74]. Successful adoption may be limited if there is a lack of awareness of the benefits to the general public [22]. Some authors identified that new or prospective participants may want to know if evidence exists of the benefits of m-health to patients [88, 89]. Patients will adopt services that address their needs and are considered satisfactory [17]. Mobile phone functions that patients viewed as beneficial included automated reminder systems, drug adherence alarms, and appointment reminders from care givers [39, 40].
Patients must feel comfortable that an m-health system will successfully deliver what they want, and will avoid adopting an m-health system they are unfamiliar with or for which there is limited evidence of effectiveness [18, 24]. Conversely, several papers reported how much patients appreciated and accepted m-health when it met their needs and made them feel valued [21, 38, 48, 90], provided reliable and timely responses that improved quality of life [87], and facilitated two-way communication between the patient and healthcare provider [26]. This phenomenon of leaving the response promptings to the digital awareness of the patients who may have low digital literacy or the benevolence of caregivers is certainly not reliable [40, 91].
An oblique observation was that inadequate monitoring and evaluation can adversely impact patient m-health adoption. Adequate evaluation and monitoring to identify technology, socio-cultural, community, and health related needs that will affect adoption if not addressed before scale-up is not always performed during the pilot stage [49, 77]. Similarly, the use of inconsistent indicators and poor evaluation methods made cost-effective uptake of m-health in the developing world difficult to prove [49]. Additionally, adoption of m-health services is facilitated through awareness (marketing and publicity of benefits and capabilities) [19, 25], and managing expectations to ensure they are realistic [22, 87].
Proposed Framework
Resources identified through the search addressed ‘m-health adoption’ issues broadly and not ‘patient m-health adoption’ issues specifically, requiring patient related issues to be teased out from the identified studies. Based on the findings, it was considered that for m-health to be maximally adopted by patients in the developing world a framework (Figure 2) in which all the above identified factors are captured must be used to guide the implementation.