Background Mobile health (mHealth) solutions have proven to be effective in a wide range of patient outcomes and have proliferated over time. However, a persistent challenge of digital health technologies, including mHealth, is that they are characterized by early dropouts in clinical practice and struggle to be used outside experimental settings or on larger scales. Objective This study aimed to explore barriers and enablers to the uptake of mHealth solutions used by patients with cancer undergoing treatment, using a theory-guided implementation science model, that is, the Consolidated Framework for Implementation Research (CFIR). Methods A scoping literature review was conducted using PubMed (MEDLINE), Web of Science, and ScienceDirect databases in March 2022. We selected studies that analyzed the development, evaluation, and implementation of mHealth solutions for patients with cancer that were used in addition to the standard of care. Only empirical designs (eg, randomized controlled trials, observational studies, and qualitative studies) were considered. First, information on the study characteristics, patient population, app functionalities, and study outcomes was extracted. Then, the CFIR model was used as a practical tool to guide data collection and interpretation of evidence on mHealth uptake. Results Overall, 91 papers were included in the data synthesis. The selected records were mostly randomized controlled trials (26/91, 29%) and single-arm, noncomparative studies (52/91, 57%). Most of the apps (42/73, 58%) were designed for both patients and clinicians and could be used to support any type of cancer (29/73, 40%) and a range of oncological treatments. Following the CFIR scheme (intervention, outer setting, inner setting, individuals, process), multistakeholder co-design, codevelopment, and testing of mHealth interventions were identified as key enablers for later uptake. A variety of external drivers emerged, although the most relevant outer incentive fostering mHealth use was addressing patient needs. Among organizational factors likely to influence technology uptake, interoperability was the most prominent, whereas other providers’ dimensions such as managerial attitudes or organizational culture were not systematically discussed. Technology-related impediments that could hamper the use of mHealth at the individual level were considered least often. Conclusions The hype surrounding mHealth in cancer care is hindered by several factors that can affect its use in real world and nonexperimental settings. Compared with the growing evidence on mHealth efficacy, knowledge to inform the uptake of mHealth solutions in clinical cancer care is still scarce. Although some of our findings are supported by previous implementation research, our analysis elaborates on the distinguishing features of mHealth apps and provides an integrated perspective on the factors that should be accounted for implementation efforts. Future syntheses should liaise these dimensions with strategies observed in successful implementation initiatives.
BACKGROUND mHealth importance has been growing over time due to recent demographic and epidemiological trends and the rise of chronic conditions, enhanced smartphone hardware and software functionalities, and the need to contain healthcare spending. Yet, even when beneficial to improve patient outcomes, sustained mHealth app usage is not necessarily observed in clinical practice. OBJECTIVE This work aims at investigating barriers and enablers to continuous uptake of mHealth solutions to support the treatment stage within the continuum of cancer care. METHODS A scoping literature review has been conducted on MedLine and Web of Science databases in March 2022. Studies analyzing mHealth solutions for cancer patients under ongoing treatments were searched. Experimental study designs including RCTs, and observational studies were considered. Data on study characteristics, patient population, app functionalities, study outcomes, and implementation barriers and enablers were extracted. The Consolidated Framework for Implementation Research (CFIR) was used as a practical tool to guide data collection and analysis. Evidence was synthetized mostly with a narrative format. RESULTS Overall, 89 papers were included for data synthesis. Almost half of the studies (N=41, 46.1%) were published in Europe. The most frequent study design is RCT (N=26, 29.2%), but overall single-arm non-comparative studies (N=50, 56.2%) prevail. As for implementation barriers and enablers assessed using the CFIR, on one hand, involvement of several stakeholders in the app co-design, small scales pilot testing, and social endorsement by key opinion leaders are amongst the most relevant facilitators. On the other hand, individuals’ perceptions of smartphone use in certain social contexts (e.g., at work), a weak sense of identification with health service providers or the lack of interoperability with hospital IT systems are the most recurrent barriers. CONCLUSIONS The hype surrounding mHealth diffusion is hindered by a number of barriers and facilitators that affect its implementation in the continuum of cancer care. These elements should be systematically considered in the attempt to close the “research-do gap” between what works in principle and what is used in clinical practice, hopefully leading to a sustained use of mHealth in real life. CLINICALTRIAL None.
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