Supporting Self-Management of Cardiovascular Diseases Through Remote Monitoring Technologies: Metaethnography Review of Frameworks, Models, and Theories Used in Research and Development

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

[1]  Francine Toye,et al.  Meta-ethnography 25 years on: challenges and insights for synthesising a large number of qualitative studies , 2014, BMC Medical Research Methodology.

[2]  Alan D. Lopez,et al.  Global, Regional, and National Burden of Cardiovascular Diseases for 10 Causes, 1990 to 2015 , 2017, Journal of the American College of Cardiology.

[3]  Drasko M. Sotirovski Heuristics for Iterative Software Development , 2001, IEEE Softw..

[4]  Si‐Hyuck Kang,et al.  Enhancing User Experience Through User Study: Design of an mHealth Tool for Self-Management and Care Engagement of Cardiovascular Disease Patients , 2018, JMIR cardio.

[5]  S. Michie,et al.  The behaviour change wheel: A new method for characterising and designing behaviour change interventions , 2011, Implementation science : IS.

[6]  Lucy Yardley,et al.  Developing and Evaluating Digital Interventions to Promote Behavior Change in Health and Health Care: Recommendations Resulting From an International Workshop , 2017, Journal of medical Internet research.

[7]  Christopher Hass,et al.  A Practical Guide to Usability Testing , 2019, Consumer Informatics and Digital Health.

[8]  C. Wright,et al.  Self-management approaches for people with chronic conditions: a review. , 2002, Patient education and counseling.

[9]  S. Oliver,et al.  Enhancing transparency in reporting the synthesis of qualitative research: ENTREQ , 2012, BMC Medical Research Methodology.

[10]  Kate Flemming,et al.  Cochrane Qualitative and Implementation Methods Group guidance series-paper 3: methods for assessing methodological limitations, data extraction and synthesis, and confidence in synthesized qualitative findings. , 2017, Journal of clinical epidemiology.

[11]  Viswanath Venkatesh,et al.  Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology , 2012, MIS Q..

[12]  C. Dowrick,et al.  Complex interventions , 2022, International Review of Sport and Exercise Psychology.

[13]  Mark Engel,et al.  Conducting a meta-ethnography of qualitative literature: Lessons learnt , 2008, BMC medical research methodology.

[14]  G. Kok,et al.  Planning theory- and evidence-based behavior change interventions: a conceptual review of the intervention mapping protocol , 2017, Psicologia: Reflexão e Crítica.

[15]  A. Bandura Social Foundations of Thought and Action: A Social Cognitive Theory , 1985 .

[16]  Deborah A. Greenwood,et al.  A Systematic Review of Reviews Evaluating Technology-Enabled Diabetes Self-Management Education and Support , 2017, Journal of diabetes science and technology.

[17]  Harleah G. Buck,et al.  Self‐Care for the Prevention and Management of Cardiovascular Disease and Stroke , 2017, Journal of the American Heart Association.

[18]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[19]  Yuan Long,et al.  Synthesizing e-government stage models - a meta-synthesis based on meta-ethnography approach , 2005, Ind. Manag. Data Syst..

[20]  J. Sweeney,et al.  Patient and family engagement: a framework for understanding the elements and developing interventions and policies. , 2013, Health affairs.

[21]  Thomas M. Duffy,et al.  Problem Based Learning: An instructional model and its constructivist framework , 1995 .

[22]  Jylana L. Sheats,et al.  The Use of Behavior Change Techniques and Theory in Technologies for Cardiovascular Disease Prevention and Treatment in Adults: A Comprehensive Review. , 2016, Progress in cardiovascular diseases.

[23]  Leslie Haddon,et al.  Design and the domestication of information and communication technologies: technical change and everyday life , 1996 .

[24]  C. Carver,et al.  Control theory: a useful conceptual framework for personality-social, clinical, and health psychology. , 1982, Psychological bulletin.

[25]  Lisette van Gemert-Pijnen,et al.  Holistic development of eHealth technology , 2018 .

[26]  F. Mair,et al.  Intervention planning for a digital intervention for self-management of hypertension: a theory-, evidence- and person-based approach , 2017, Implementation Science.

[27]  A. Booth,et al.  Improving reporting of meta-ethnography: the eMERGe reporting guidance , 2019, BMC Medical Research Methodology.

[28]  J. Unützer,et al.  Health Behavior Models for Informing Digital Technology Interventions for Individuals With Mental Illness , 2017, Psychiatric rehabilitation journal.

[29]  Fadhel Kaboub Realistic Evaluation , 2004 .

[30]  Richard J. Holden,et al.  Human Factors Analysis, Design, and Evaluation of Engage, a Consumer Health IT Application for Geriatric Heart Failure Self-Care , 2017, Int. J. Hum. Comput. Interact..

[31]  Nick Allcock,et al.  A meta-ethnography of patients’ experience of chronic non-malignant musculoskeletal pain , 2013 .

[32]  Marcus Foth,et al.  Action Research in the Design of New Media and ICT Systems , 2005 .

[33]  Trisha Greenhalgh,et al.  Beyond Adoption: A New Framework for Theorizing and Evaluating Nonadoption, Abandonment, and Challenges to the Scale-Up, Spread, and Sustainability of Health and Care Technologies , 2017, Journal of medical Internet research.

[34]  M. Maxwell,et al.  A methodological systematic review of meta-ethnography conduct to articulate the complex analytical phases , 2019, BMC Medical Research Methodology.

[35]  L. Yardley,et al.  The Person-Based Approach to Intervention Development: Application to Digital Health-Related Behavior Change Interventions , 2015, Journal of medical Internet research.

[36]  M. R. Anusree,et al.  Business Research Methods: An Applied Orientation , 2013 .

[37]  Ponrathi Athilingam,et al.  "Mobile technology to improve heart failure outcomes: A proof of concept paper". , 2018, Applied nursing research : ANR.

[38]  David Weller,et al.  Telehealth Interventions to Support Self-Management of Long-Term Conditions: A Systematic Metareview of Diabetes, Heart Failure, Asthma, Chronic Obstructive Pulmonary Disease, and Cancer , 2017, Journal of medical Internet research.

[39]  Carmelo Velardo,et al.  Creating connections – the development of a mobile-health monitoring system for heart failure: Qualitative findings from a usability cohort study , 2016, Digital health.

[40]  E. Deci,et al.  Facilitating health behaviour change and its maintenance: Interventions based on Self-Determination Theory , 2008 .

[41]  John Sweller,et al.  Cognitive Load During Problem Solving: Effects on Learning , 1988, Cogn. Sci..

[42]  Fred D. Davis,et al.  Dead Or Alive? The Development, Trajectory And Future Of Technology Adoption Research , 2007, J. Assoc. Inf. Syst..

[43]  M. Jessup,et al.  Understanding Heart Failure. , 2017, Heart failure clinics.

[44]  Radhika Jain,et al.  Agile Software Development: Adaptive Systems Principles and Best Practices , 2006, Inf. Syst. Manag..

[45]  Harri Oinas-Kukkonen,et al.  Persuasive Systems Design: Key Issues, Process Model, and System Features , 2009, Commun. Assoc. Inf. Syst..

[46]  L. A. Phillips,et al.  The Common-Sense Model of Self-Regulation (CSM): a dynamic framework for understanding illness self-management , 2016, Journal of Behavioral Medicine.

[47]  J. Wyatt,et al.  Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide , 2014, BMJ : British Medical Journal.

[48]  Jerry Suls,et al.  The value of a second reviewer for study selection in systematic reviews , 2019, Research synthesis methods.

[49]  Carmelo Velardo,et al.  A personalised mobile-based home monitoring system for heart failure: The SUPPORT-HF Study , 2015, Int. J. Medical Informatics.

[50]  C. Pope,et al.  Evaluating meta-ethnography: systematic analysis and synthesis of qualitative research. , 2011, Health technology assessment.

[51]  G. Kok,et al.  Intervention Mapping - Designing Theory and Evidence-Based Health Promotion Programs , 2000 .

[52]  Claudia Pagliari,et al.  Design and Evaluation in eHealth: Challenges and Implications for an Interdisciplinary Field , 2007, Journal of medical Internet research.

[53]  Alan Cooper,et al.  About Face 3: the essentials of interaction design , 1995 .

[54]  Claes Wohlin,et al.  Experiences from using snowballing and database searches in systematic literature studies , 2015, EASE.

[55]  E. Deci,et al.  Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. , 2000, The American psychologist.

[56]  Jack Parker,et al.  The SMART personalised self-management system for congestive heart failure: results of a realist evaluation , 2014, BMC Medical Informatics and Decision Making.

[57]  S. Read Applications of Case Study Research , 2003 .

[58]  A. Farmer,et al.  Designing and evaluating complex interventions to improve health care , 2007, BMJ : British Medical Journal.

[59]  Debbie Sharp,et al.  "Medication career" or "moral career"? The two sides of managing antidepressants: a meta-ethnography of patients' experience of antidepressants. , 2009, Social science & medicine.

[60]  Tiziana Catarci,et al.  A Three-Fold Integration Framework to Incorporate User-Centered Design into Agile Software Development , 2011, HCI.

[61]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[62]  Noel O'Connor,et al.  MedFit App, a Behavior-Changing, Theoretically Informed Mobile App for Patient Self-Management of Cardiovascular Disease: User-Centered Development , 2018, JMIR formative research.

[63]  Richard J. Holden,et al.  Human Factors Engineering and Human–Computer Interaction: Supporting User Performance and Experience , 2016 .

[64]  E. Erasmus The use of street-level bureaucracy theory in health policy analysis in low- and middle-income countries: a meta-ethnographic synthesis. , 2014, Health policy and planning.

[65]  M. Labrador,et al.  Intervention Mapping Approach in the Design of an Interactive Mobile Health Application to Improve Self-care in Heart Failure , 2017, Computers, informatics, nursing : CIN.

[66]  R. Galvin,et al.  Qualitative synthesis: A guide to conducting a meta-ethnography , 2018 .

[67]  Lucy Yardley,et al.  Understanding how primary care practitioners perceive an online intervention for the management of hypertension , 2017, BMC Medical Informatics and Decision Making.

[68]  William A. Fisher,et al.  The Information‐Motivation‐Behavioral Skills Model: A General Social Psychological Approach to Understanding and Promoting Health Behavior , 2009 .

[69]  Dario Salvi,et al.  Validation Results of the User Interaction in a Heart Failure Management System , 2009, 2009 International Conference on eHealth, Telemedicine, and Social Medicine.

[70]  H. Dominic Covvey,et al.  Healthcare as a complex adaptive system , 2018 .

[71]  V. Cornelissen,et al.  Electronic Health Physical Activity Behavior Change Intervention to Self-Manage Cardiovascular Disease: Qualitative Exploration of Patient and Health Professional Requirements. , 2017, Journal of medical Internet research.

[72]  Amiram Gafni,et al.  Designing, Implementing, and Evaluating Mobile Health Technologies for Managing Chronic Conditions in Older Adults: A Scoping Review , 2016, JMIR mHealth and uHealth.

[73]  Jouni Ikonen,et al.  Cloud-based bibliometric analysis service for systematic mapping studies , 2015, CompSysTech '15.

[74]  Josefien van Olmen,et al.  Is realist evaluation keeping its promise? A review of published empirical studies in the field of health systems research , 2012 .

[75]  A. Niroshan Siriwardena,et al.  Perceptions on use of home telemonitoring in patients with long term conditions – concordance with the Health Information Technology Acceptance Model: a qualitative collective case study , 2017, BMC Medical Informatics and Decision Making.

[76]  D. Moher,et al.  Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. , 2010, International journal of surgery.

[77]  Sidney Fels,et al.  A framework for evaluating usability of clinical monitoring technology , 2007, Journal of Clinical Monitoring and Computing.

[78]  Joon Lee,et al.  Smart Devices for Older Adults Managing Chronic Disease: A Scoping Review , 2017, JMIR mHealth and uHealth.

[79]  David F. Gleich,et al.  PageRank beyond the Web , 2014, SIAM Rev..

[80]  A. Bandura Health Promotion by Social Cognitive Means , 2004, Health education & behavior : the official publication of the Society for Public Health Education.

[81]  M. Johansen,et al.  Factors Determining the Success and Failure of eHealth Interventions: Systematic Review of the Literature , 2018, Journal of medical Internet research.

[82]  M. Malbrán The Cambridge Handbook of Multimedia Learning , 2007 .

[83]  R. Silverstone,et al.  Consuming technologies : media and information in domestic spaces , 1993 .

[84]  Roxana Moreno,et al.  The Cambridge Handbook of Multimedia Learning: Multimedia Learning with Animated Pedagogical Agents , 2005 .

[85]  Predrag V. Klasnja,et al.  Mind the theoretical gap: interpreting, using, and developing behavioral theory in HCI research , 2013, CHI.

[86]  J. Raftery,et al.  Home and Online Management and Evaluation of Blood Pressure (HOME BP) digital intervention for self-management of uncontrolled, essential hypertension: a protocol for the randomised controlled HOME BP trial , 2016, BMJ Open.

[87]  S. Dopson,et al.  Factors influencing the adoption of self-management solutions: an interpretive synthesis of the literature on stakeholder experiences , 2015, Implementation Science.

[88]  C. Pope,et al.  Medicine Taking for Asthma: A Worked Example of Meta‐Ethnography , 2012 .

[89]  Tiffany C. Veinot,et al.  Transforming consumer health informatics through a patient work framework: connecting patients to context , 2015, J. Am. Medical Informatics Assoc..

[90]  Elizabeth Murray,et al.  Using digital interventions for self-management of chronic physical health conditions: A meta-ethnography review of published studies. , 2017, Patient education and counseling.

[91]  R. Mayer,et al.  Cognitive Principles of Multimedia Learning: The Role of Modality and Contiguity , 1999 .

[92]  Chia-Chien Hsu,et al.  The Delphi Technique: Making Sense of Consensus , 2007 .

[93]  Meta-ethnography and systematic reviews – linked to the evidence movement and caught in a dilemma , 2017 .

[94]  Robert West,et al.  The Behaviour Change Wheel: A Guide To Designing Interventions , 2014 .

[95]  Kate Flemming,et al.  Guidance on choosing qualitative evidence synthesis methods for use in health technology assessments of complex interventions , 2016 .

[96]  C. Pope,et al.  Using meta ethnography to synthesise qualitative research: a worked example , 2002, Journal of health services research & policy.

[97]  Ponrathi Athilingam,et al.  Features and usability assessment of a patient-centered mobile application (HeartMapp) for self-management of heart failure. , 2016, Applied nursing research : ANR.

[98]  Andrew F. Monk,et al.  User-Centred Design , 2000, Encyclopedia of Database Systems.

[99]  P. Carayon,et al.  SEIPS 2.0: a human factors framework for studying and improving the work of healthcare professionals and patients , 2013, Ergonomics.

[100]  Ioanna Chouvarda,et al.  The development and codesign of the PATHway intervention: a theory-driven eHealth platform for the self-management of cardiovascular disease. , 2019, Translational behavioral medicine.

[101]  T. Greenhalgh,et al.  Understanding heart failure; explaining telehealth – a hermeneutic systematic review , 2017, BMC Cardiovascular Disorders.

[102]  C. May A rational model for assessing and evaluating complex interventions in health care , 2006, BMC Health Services Research.

[103]  Nicol Nijland,et al.  A Holistic Framework to Improve the Uptake and Impact of eHealth Technologies , 2011, Journal of medical Internet research.

[104]  Mathew Gregoski,et al.  Facilitating medication adherence and eliminating therapeutic inertia using wireless technology: proof of concept findings with uncontrolled hypertensives and kidney transplant recipients , 2012, Wireless Health.

[105]  Whitney Quesenbery,et al.  Dimensions of Usability: Defining the Conversation, Driving the Process , 2003 .

[106]  Vijay N. Nair,et al.  A strategy for optimizing and evaluating behavioral interventions , 2005, Annals of behavioral medicine : a publication of the Society of Behavioral Medicine.

[107]  M. Petticrew,et al.  Developing and evaluating complex interventions: the new Medical Research Council guidance , 2008, BMJ : British Medical Journal.

[108]  Richard E. Mayer,et al.  A Cognitive Theory of Multimedia Learning: Implications for Design Principles , 2001 .

[109]  Carmelo Velardo,et al.  A user-centred home monitoring and self-management system for patients with heart failure: a multicentre cohort study. , 2015, European heart journal. Quality of care & clinical outcomes.

[110]  Dario Salvi,et al.  Iterative User Interaction Design for Wearable and Mobile Solutions to assess Cardiovascular Chronic Diseases , 2008 .

[111]  Bret R. Shaw,et al.  Relevance of CONSORT reporting criteria for research on eHealth interventions. , 2010, Patient education and counseling.

[112]  G. Eysenbach CONSORT-EHEALTH: Improving and Standardizing Evaluation Reports of Web-based and Mobile Health Interventions , 2011, Journal of medical Internet research.

[113]  Lucy Yardley,et al.  The person-based approach to enhancing the acceptability and feasibility of interventions , 2015, Pilot and Feasibility Studies.

[114]  Roberto Rafael Cruz-Martínez,et al.  Frameworks, Models, and Theories Used in Electronic Health Research and Development to Support Self-Management of Cardiovascular Diseases Through Remote Monitoring Technologies: Protocol for a Metaethnography Review , 2019, JMIR research protocols.

[115]  Jackie MacDonald,et al.  Systematic Approaches to a Successful Literature Review , 2014 .

[116]  Ralph Maddison,et al.  A Development and Evaluation Process for mHealth Interventions: Examples From New Zealand , 2012, Journal of health communication.

[117]  Richard Winter,et al.  A handbook for action research in health and social care , 2001 .

[118]  A. Booth,et al.  Improving reporting of meta‐ethnography: The eMERGe reporting guidance , 2019, Psycho-oncology.

[119]  C. Dowrick,et al.  Process evaluation for complex interventions in primary care: understanding trials using the normalization process model , 2007, BMC family practice.