Background Electronic health (eHealth) is a rapidly evolving field informed by multiple scientific disciplines. Because of this, the use of different terms and concepts to explain the same phenomena and lack of standardization in reporting interventions often leaves a gap that hinders knowledge accumulation. Interventions focused on self-management support of cardiovascular diseases through the use of remote monitoring technologies are a cross-disciplinary area potentially affected by this gap. A review of the underlying frameworks, models, and theories that have informed projects at this crossroad could advance future research and development efforts. Objective This research aimed to identify and compare underlying approaches that have informed interventions focused on self-management support of cardiovascular diseases through the use of remote monitoring technologies. The objective was to achieve an understanding of the distinct approaches by highlighting common or conflicting principles, guidelines, and methods. Methods The metaethnography approach was used to review and synthesize researchers’ reports on how they applied frameworks, models, and theories in their projects. Literature was systematically searched in 7 databases: Scopus, Web of Science, EMBASE, CINAHL, PsycINFO, Association for Computing Machinery Digital Library, and Cochrane Library. Included studies were thoroughly read and coded to extract data for the synthesis. Studies were mainly related by the key ingredients of the underlying approaches they applied. The key ingredients were finally translated across studies and synthesized into thematic clusters. Results Of 1224 initial results, 17 articles were included. The articles described research and development of 10 different projects. Frameworks, models, and theories (n=43) applied by the projects were identified. Key ingredients (n=293) of the included articles were mapped to the following themes of eHealth development: (1) it is a participatory process; (2) it creates new infrastructures for improving health care, health, and well-being; (3) it is intertwined with implementation; (4) it integrates theory, evidence, and participatory approaches for persuasive design; (5) it requires continuous evaluation cycles; (6) it targets behavior change; (7) it targets technology adoption; and (8) it targets health-related outcomes. Conclusions The findings of this review support and exemplify the numerous possibilities in the use of frameworks, models, and theories to guide research and development of eHealth. Participatory, user-centered design, and integration with empirical evidence and theoretical modeling were widely identified principles in the literature. On the contrary, less attention has been given to the integration of implementation in the development process and supporting novel eHealth-based health care infrastructures. To better integrate theory and evidence, holistic approaches can combine patient-centered studies with consolidated knowledge from expert-based approaches. Trial Registration PROSPERO CRD42018104397; https://tinyurl.com/y8ajyajt International Registered Report Identifier (IRRID) RR2-10.2196/13334
Background Electronic health (eHealth) is a multidisciplinary and rapidly evolving field, and thus requires research focused on knowledge accumulation, curation, and translation. Cardiovascular diseases constitute a global health care crisis in which eHealth can provide novel solutions to improve the efficiency and reach of self-management support for patients where they most need it: their homes and communities. A holistic understanding of eHealth projects focused on such case is required to bridge the multidisciplinary gap formed by the wide range of aims and approaches taken by the various disciplines involved. Objective The primary objective of this review is to facilitate a holistic interpretation of eHealth projects aimed at providing self-management support of cardiovascular diseases in the natural setting of patients, thus priming the use of remote monitoring technologies. The review aims to synthesize the operationalization of frameworks, models, and theories applied to the research and development process of eHealth. Methods We will use Noblit and Hare’s metaethnography approach to review and synthesize researchers’ and practitioners’ reports on how they applied frameworks, models, and theories in their projects. We will systematically search the literature in 7 databases: Scopus, Web of Science, EMBASE, CINAHL, PsycINFO, ACM Digital Library, and the Cochrane Library. We will thoroughly read and code selected studies to extract both raw and contextual data for the synthesis. The relation of the studies will be determined according to the elements of the frameworks, models, or theories the studies applied. We will translate these elements between each other and intend to synthesize holistic principles for eHealth development for the case at hand. Results The search strategy has been completed, data extraction is almost finalized, and the first synthesis approaches are underway. The search yielded 1224 citations and, after we applied the selection criteria, 17 articles remained. We expect to submit the final results for publication in 2019. Conclusions This review is important because it aims to create a holistic understanding of a multidisciplinary topic at the crossroads of eHealth, cardiovascular diseases, and self-management. The value of metaethnography in contrast to other systematic review methods is that its synthesis approach seeks to generate a new understanding of a topic, while preserving the social and theoretical contexts in which findings emerge. Our results will show how useful this method can be in bridging the multidisciplinary gap of eHealth research and development, to inform and advance the importance of holistic approaches, while showcasing this approach for the case of self-management in cardiovascular diseases. Trial Registration PROSPERO CRD42018104397; https://www.crd.york.ac.uk/PROSPERO/display_record.php? RecordID=10439...
Self-care support is a key cornerstone of treatment for patients with a cardiovascular disease. The success of any supportive intervention requires adaptation to the distinct needs of individuals. This requirement also applies to eHealth interventions. This study investigates how experts from multiple fields of science assess the potential success of different eHealth design strategies when matched to key self-care needs. An online vignette survey experiment was conducted. Nine vignettes representing different combinations of self-care needs (maintenance, monitoring, management) and eHealth persuasive design strategies (primary task support, dialogue support, social support) were evaluated. In total, 118 experts from 18 different countries participated in the survey. Their evaluations show primary task support as a promising design strategy across all self-care needs. In contrast, dialogue support and social support showed more promise for specific self-care needs. Above all, according to experts, the success of design strategies could be enhanced by (i) personalising the pacing of the intervention and (ii) tailoring the information to the literacy and culture of the person. Adding to that, self-care support should distinctly (iii) support the three self-care needs, be (iv) patient-centered, (v) support the collaboration with caregivers, and (vi) be aligned to the life goals and values of individuals.
Background eHealth can revolutionize the way self-management support is offered to chronically ill individuals such as those with a cardiovascular disease (CVD). However, patients’ fluctuating motivation to actually perform self-management is an important factor for which to account. Tailoring and personalizing eHealth to fit with the values of individuals promises to be an effective motivational strategy. Nevertheless, how specific eHealth technologies and design features could potentially contribute to values of individuals with a CVD has not been explicitly studied before. Objective This study sought to connect a set of empirically validated, health-related values of individuals with a CVD with existing eHealth technologies and their design features. The study searched for potential connections between design features and values with the goal to advance knowledge about how eHealth technologies can actually be more meaningful and motivating for end users. Methods Undertaking a technical investigation that fits with the value sensitive design framework, a content analysis of existing eHealth technologies was conducted. We matched 11 empirically validated values of CVD patients with 70 design features from 10 eHealth technologies that were previously identified in a systematic review. The analysis consisted mainly of a deductive coding stage performed independently by 3 members of the study team. In addition, researchers and developers of 6 of the 10 reviewed technologies provided input about potential feature-value connections. Results In total, 98 connections were made between eHealth design features and patient values. This meant that some design features could contribute to multiple values. Importantly, some values were more often addressed than others. CVD patients’ values most often addressed were related to (1) having or maintaining a healthy lifestyle, (2) having an overview of personal health data, (3) having reliable information and advice, (4) having extrinsic motivators to accomplish goals or health-related activities, and (5) receiving personalized care. In contrast, values less often addressed concerned (6) perceiving low thresholds to access health care, (7) receiving social support, (8) preserving a sense of autonomy over life, and (9) not feeling fear, anxiety, or insecurity about health. Last, 2 largely unaddressed values were related to (10) having confidence and self-efficacy in the treatment or ability to achieve goals and (11) desiring to be seen as a person rather than a patient. Conclusions Positively, existing eHealth technologies could be connected with CVD patients’ values, largely through design features that relate to educational support, self-monitoring support, behavior change support, feedback, and motivational incentives. Other design features such as reminders, prompts or cues, peer-based or expert-based human support, and general system personalization were also connected with values but in narrower ways. In future studies, the inferred feature-value connections must be validated with empirical data from individuals with a CVD or similar chronic conditions.
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