The purpose of scoping reviews includes comprehensively synthesizing evidence to map a broad, complex, or emerging field of study and to identify gaps with the intent to inform practice, policy, and future research [47]. A scoping review methodology was chosen as a tool for systematically mapping and disseminating the breadth of research available to address the broad, complex, and novel research question, “What are the current practices and recommendations for designing, implementing, and evaluating mHealth solutions to support older adults with chronic conditions living in their homes?” More specifically, this review considers solutions that enable care-related communication, information sharing, and information access for older adults and those involved in the care of older adults with chronic conditions living in their homes. This includes technologies intended for use by health care providers (HCPs), family, significant others, and friends involved in care, as well as older adults themselves. HCPs include all health professionals as well as unregulated providers such as personal support workers. This review, as is appropriate with a scoping review methodology, encompasses a broad range of study designs and varied contexts including different countries, communities, technologies, implementation milieus, and chronic conditions/stages without separating those with single conditions from those with multiple chronic conditions.

To complete this scoping review, we followed the five-stage framework developed by Arskey and O’Malley [47] and further defined by Levac, Colquhoun, and O’Brien [48]. The stages include: (1) identification of the research question, (2) identification of relevant studies, (3) selection of relevant studies for the review, (4) charting information and data from the selected literature, and (5) summarizing and reporting the results of the review.

The research question was identified from a preliminary scan of the literature and drawing on the expertise of the research team and several stakeholders. Rationale for the question arose from the lack of existing consensus in the academic literature on designing, implementing, and evaluating mHealth solutions in community-based settings, specifically as it pertains to older adults living at home with chronic conditions.

The team collaboratively planned and implemented a search strategy to identify relevant literature that was specific to mHealth solutions targeting chronic conditions and community-based care of older adults. Keywords and related subject headings were identified in consultation with research librarians in order to capture a comprehensive list of potential sources. Keywords were identified and combined to address three components of the research question: (1) mobile or electronic devices, (2) technology-based health care delivery, and (3) an aging population and/or chronic conditions (Textbox 1). Keywords were searched using Boolean operators. The databases used to locate the relevant literature were the following: Cochrane Library, Embase, PsychInfo, Medline, and CINAHL. Databases were searched for English language articles published between January 2005 and March 2015. In addition, reference lists were searched and a key journal hand search was completed (Journal of Medical Internet Research). Only articles published in peer-reviewed scientific journals were considered for review.

Two reviewers independently searched the titles and abstracts of the retrieved literature. Conflicts were resolved by a third reviewer and through team consensus. Inclusion criteria were mHealth technologies focusing on at least one of the following: (1) chronic conditions associated with aging populations, (2) HCPs providing home care, and/or (3) older adults living at home and/or their informal caregivers. Research articles using different methodologies (qualitative, quantitative, and systematic reviews) as well as theoretical papers were included and all papers had to be in English. The exclusion criteria were the following: (1) mHealth solutions being used for diagnostics/imaging, acute care, body and environment monitoring or support devices, or robotics; (2) technology pertaining to healthcare in developing countries; and (3) non-English language publications. Methodological quality of the published articles was not a criterion for exclusion/inclusion. This enabled the inclusion of a breadth of knowledge pertaining to the research question, as is consistent with scoping review practices [47-49].

Articles that potentially met inclusion criteria through abstract review were reviewed in full by team members. Meetings were held regularly to discuss reviewers' decisions specific to the inclusion and/or exclusion of articles. Both inclusion and exclusion criteria were revised as the search evolved, in order to best address the research question. Under the final revised criteria, only articles pertaining to older adults (>50 years old) with one or more chronic conditions living in their homes were included.

A descriptive-analytical narrative method was used to extract and chart the data from the selected articles [47-49]. Using the same process of team consultation, data from the selected articles were first extracted onto a data charting form developed by the research team using an iterative process. Charts were used to collate, summarize, and share data for team review and decision making. Data entered included the following: authors, year of publication, purpose of the paper/study and innovation, study location and context (setting, end-users of innovation), study design, outcomes measured, main findings, and lessons learned. A coding scheme (framework) was created under four thematic categories: (1) design and development, (2) implementation, (3) evaluation, and (4) risks and benefits. Full articles were imported as pdf files into NVivo 10, a software program for qualitative analysis, for more detailed data extraction and coding. The authors applied the coding scheme to all pertinent text, and then further coded the data under emergent themes using an iterative process.

In total, 1021 published articles were identified in the database search (Figure 1) and of these, 811 were excluded based on a review of titles and abstracts. Of the remaining 210, another 183 including 29 duplicates were excluded through independent review followed by team reviewer consensus, leaving a total of 27 articles. Ten more articles found through reference list reviews plus 5 articles found through a manual search of a key journal (Journal of Medical Internet Research) were accepted after applying inclusion/exclusion criteria. A total of 42 sources were included in this review.

Of the 42 studies included (Table 1), 9 were from the United States, 5 from Canada, 5 from the United Kingdom, 6 from Scandinavian countries (Denmark=3, Norway=1, Finland=1, Sweden=1), 3 from the Netherlands, 4 from Australia, 2 from New Zealand, 4 from East Asia (South Korea=1, Japan=1, Taiwan=2), and 1 each from China, Italy, Belgium, and Poland.

Seven of the selected articles were theoretical papers (discussion and position papers). Four were descriptive reports of existing interventions, and 3 were case studies describing processes of mHealth implementation. Two articles described predictive modeling techniques for screening patients in use of technology. Three qualitative descriptive studies elicited opinions concerning mHealth. There were 13 papers in which mHealth solutions were evaluated; 6 controlled trials, 3 mixed-methods studies, and 4 qualitative studies. Three studies were cross-sectional surveys, 3 were systematic or scoping reviews, 2 were methods papers, and 1 paper focused on simulation.

Of the 42 articles, 17 focused on older adults with single chronic conditions: diabetes (n=4), stroke (n=5), heart condition (n=4), COPD (n=1), and dementia or cognitive impairment (n=3). Six articles involved older adults with any chronic condition or multiple chronic conditions. Conditions were not specified in 18 articles, in some cases referencing older adults (n=5) or home care patients (n=6) and caregiver burden (n=1).

The majority of mHealth solutions described were designed for use by both patients and HCPs (n=19), followed by HCPs only (n=7), patients only (n=5), caregivers, patients, and HCPs (n=4), and patients and caregivers (n=3); one mHealth solution was targeted exclusively at family caregivers. The remaining 3 articles were nonspecific.

Results pertaining to mHealth solutions are organized under 3 phases of development: design, implementation, and evaluation. Given the iterative and cyclical nature of designing, implementing, and evaluating mHealth technologies, these categories are not discrete entities and inevitably overlap. The categorical terms were used to organize the review findings as commonly presented in the papers reviewed. Each section is discussed within thematic constructs derived from the analysis of the selected literature using an iterative process of qualitative content review.

Two thematic constructs emerged from the literature pertaining to practices and considerations in designing mHealth solutions: (1) user-centered design and (2) interdisciplinary/collaborative team approaches.

Three thematic constructs emerged from the literature pertaining to successfully implementing mHealth solutions: (1) feasibility in relation to organizational and systems readiness, (2) acceptability of the mHealth solution, and (3) usability in relation to the different end-users. These factors were reported to either facilitate or hinder the implementation of mHealth solutions.

A variety of quantitative, qualitative, and mixed-methods designs were used to evaluate mHealth solutions for older adults living at home. Researchers were interested in evaluating aspects of application design and implementation (eg, feasibility, acceptability, and usability), as well as health outcomes experienced by clients receiving the interventions (Table 2). Selected approaches used to evaluate mHealth solutions were grouped under 3 thematic constructs: (1) design and formative evaluation; (2) implementation, process, and outcome evaluation; and (3) frameworks for planning evaluation.

The findings from this review have implications for all stakeholders including researchers, clinicians, homecare providers, software developers, patients, and their families. In one of the few widespread technology implementation studies in community health care, it was clear that the extent of technology adoption was related to the end-users’ perceived value or perceived risk of using the technology [73]. This supports one of the core constructs of normalization process theory pertaining to coherence or sense-making of the innovation [87]. It is therefore vital that clinicians, researchers, and mHealth designers consider hardware and software factors in the context of end-users’ needs, preferences, and activities to ensure the solution is working for the user and not the other way around. Developers should strategically put together a team that has the capacity, including knowledge, skills, and resources to implement and maintain mHealth solutions, and who can speak to the specific needs of HCPs, patients, and their family supporters.

In only a few of the articles reviewed, were considerations and findings guided and presented within a theoretical framework [46,51,62,77]. The use of a framework enabled an approach that acknowledges the complexity of mHealth development when involving a diverse set of stakeholders and their interests in the midst of dramatic change in health care delivery. The magnitude of this challenge becomes more acute when we recognize the different levels of support required for older adults living at home—from total independence with the option to use mHealth technology as desired, to a gradation of dependency requiring the involvement of informal caregivers and health care providers. Further, the development of mHealth solutions presents its own unique challenges compared to traditional supports for older adults, when considering the kinds of expertise and systems adjustment required.

There are considerable implications for the patient when mHealth solutions are deployed within the context of health care. Researchers noted end-user concerns about implementing solutions in health care related to the idea of technology replacing, rather than supporting, human contact [73]. Accordingly, developers and health care providers must be sensitive to the needs and preferences of the patient and design solutions [54]. Patients, particularly older adults, have various levels of interest or literacy in technology; consequently, technology support needs to be factored into implementation plans [56]. In other words, mHealth is not a “one size fits all” approach.

Finally, there are policy implications at a population level. Mobile health has the potential to gather large amounts of health data that can be used to better inform interventions and care plans. However, there are many barriers to implementation and sustainability that limit the number of successful, evidence-based mHealth solutions that are implemented beyond the pilot or feasibility stage. For example, the additional costs of privacy / security testing, ongoing technology support/development, and software maintenance are a poor fit with government-supported funding cycles for research and development, where funds are typically delivered for a limited number of months or years [46].

While this scoping review highlights a number of key design principles and lessons learned for the development and implementation of mHealth solutions, there remain a number of gaps in the literature that should be addressed within future research priorities. First, there is little focus on sustainability of mHealth solutions, and few resources available for researchers to access when navigating the options and planning a sustainability plan. To address this, there may be opportunities for partnerships between industry and research to support the sustainability of an mHealth solution [46]. Second, there are few resources to support evaluating the long-term effect of using mHealth solutions. While the goals and objectives of each solution will vary, researchers would benefit from a theoretical framework to guide the cyclical, iterative process of design, implementation, and evaluation of mHealth technologies as whole entities rather than segmented parts. To this end, longer-term cohort studies and other research designs are needed that can attribute health outcomes to mHealth interventions within complex systems of health care. From a fiscal perspective, studies need to be designed that take into account the cost-effectiveness of new technologies [79].

Researchers also need to consider the unanticipated consequences and risks of mHealth solutions, as well as the potential inequities that may be created given unequal access and use of technologies in society. Potential risks to be considered include the following: (1) the potential for breaches in patient privacy and confidentiality [67,71], (2) the potential for mHealth solutions to replace rather than supplement clinical care [52], and (3) insufficient support or supervision for technologically assisted home-care rehabilitation [81]. It is critical that these risks and concerns, along with those yet unrecognized, are identified in order to manage them appropriately when any new intervention, and particularly technology-based interventions are implemented.

There is limited knowledge about the implementation science related to the adoption and acceptance of new technology in relation to home-based care for older adults. Researchers would benefit from a framework to evaluate the effectiveness of the process of implementing the mHealth solution. For example, where/when/how is support required by patients and their caregivers and how is this best addressed? More focused consideration needs to be given to patient empowerment using mHealth technology for self-management [88,89]. Further, researchers need to anticipate changing needs with different forms of technological experiences within an aging population. Investigators should consider how mHealth solutions targeted for older adults will need to evolve over time as age cohorts and technologies advance.

Various limitations concerning this review need to be considered. First, true to scoping review methods, a quality assessment of selected papers was not used to exclude articles, although all were peer-reviewed. Results from studies using a variety of study designs as well as author opinions were incorporated into the findings of this review. Second, mHealth is a rapidly advancing field. Application of the reported findings may need to be reappraised within the context of a changing landscape of innovation. Third, this scoping review addresses a broad area of content and contexts, that is, different mHealth solutions, goals, and implementation contexts; multiple applications; different users, communities, and countries; and different chronic conditions with rare separation of single conditions from the context of multiple chronic conditions. This may limit transferability of the results to a specific context and present as prime areas for future systematic and realist reviews. Fourth, grey literature is not included; sources for this review were limited to articles published in peer-reviewed journals. Unpublished yet related information on the most current trends in this field may have been missed.

Developing effective mobile technologies with minimized risk to the quality of health care offered to older adults is a current research priority. Despite the potential benefits that mHealth solutions could offer, there is limited use of these technologies in the home. Interdisciplinary mHealth development teams need to consider specific factors when designing, implementing, and evaluating such technologies that will ultimately fit within the unique context of older adults at home and their care providers. Whether the target of mHealth solutions is the patient, family and/or HCPs, it is imperative to be working with these end-users rather than for them when designing, implementing, or evaluating mHealth solutions. Optimally, the cyclical and iterative process of mHealth development needs to be viewed as a whole with supportive frameworks to foster this.

The question and selection criteria for this review allowed for a broad range of mHealth technologies to be considered that apply to a variety of chronic conditions associated with aging. This paper presents some commonalities across these different contexts using thematic constructs to inform interconnected processes of design, implementation, and evaluation when developing mHealth solutions best suited to the needs of older adults living at home. At a time of rapid technological innovation, guidelines for research and development in mHealth need to be adaptable to continuous change as new tools become available [90], even as the health care delivery system itself experiences transitions toward community care. With the development of effective and efficient evidence-based technologies, mHealth solutions offer great potential for optimizing the health of an aging population.