PDF herunterladen
Appl Clin Inform 2020; 11(04): 544-555
DOI: 10.1055/s-0040-1715649
Review Article

Influence of Connected Health Interventions for Adherence to Cardiovascular Disease Prevention: A Scoping Review

Dahbia Agher
1   INSERM, University Sorbonne Paris Nord, Sorbonne University, Laboratory of Medical Informatics and Knowledge Engineering in e-Health, LIMICS, Paris, France
2   BeWellConnect, Research and Development, Visiomed Group 75016 Paris, France
,
Karima Sedki
1   INSERM, University Sorbonne Paris Nord, Sorbonne University, Laboratory of Medical Informatics and Knowledge Engineering in e-Health, LIMICS, Paris, France
,
Rosy Tsopra
3   INSERM, Université Paris Descartes, Sorbonne Université, Centre de Recherche des Cordeliers, Information Sciences to support Personalized Medicine, F-75006 Paris, France
4   Department of Medical Informatics, H⊚pital Européen Georges-Pompidou, AP-HP, Paris, France
,
Sylvie Despres
1   INSERM, University Sorbonne Paris Nord, Sorbonne University, Laboratory of Medical Informatics and Knowledge Engineering in e-Health, LIMICS, Paris, France
,
Marie-Christine Jaulent
1   INSERM, University Sorbonne Paris Nord, Sorbonne University, Laboratory of Medical Informatics and Knowledge Engineering in e-Health, LIMICS, Paris, France
› Institutsangaben
› Weitere Informationen
   Lizenzen und Reprints

Abstract

Background Recent health care developments include connected health interventions to improve chronic disease management and/or promote actions reducing aggravating risk factors for conditions such as cardiovascular diseases. Adherence is one of the main challenges for ensuring the correct use of connected health interventions over time.

Objective This scoping review deals with the connected health interventions used in interventional studies, describing the ways in which these interventions and their functions effectively help patients to deal with cardiovascular risk factors over time, in their own environments. The objective is to acquire knowledge and highlight current trends in this field, which is currently both productive and immature.

Methods A structured literature review was constructed from Medline-indexed journals in PubMed. We established inclusion criteria relating to three dimensions (cardiovascular risk factors, connected health interventions, and level of adherence). Our initial search yielded 98 articles; 78 were retained after screening on the basis of title and abstract, 49 articles underwent full-text screening, and 24 were finally retained for the analysis, according to preestablished inclusion criteria. We excluded studies of invasive interventions and studies not dealing with digital health. We extracted a description of the connected health interventions from data for the population or end users.

Results We performed a synthetic analysis of outcomes, based on the distribution of bibliometrics, and identified several connected health interventions and main characteristics affecting adherence. Our analysis focused on three types of user action: to read, to do, and to connect. Finally, we extracted current trends in characteristics: connect, adherence, and influence.

Conclusion Connected health interventions for prevention are unlikely to affect outcomes significantly unless other characteristics and user preferences are considered. Future studies should aim to determine which connected health design combinations are the most effective for supporting long-term changes in behavior and for preventing cardiovascular disease risks.

Keywords

cardiovascular disease - adherence - connected health intervention

Authors' Contributions

All the authors contributed substantially to the design of the study and the acquisition, analysis, and/or interpretation of the data. The paper was drafted by the first author and critically reviewed by all the remaining authors. All the authors approved the final version.


Protection of Human and Animal Subjects

Not applicable.


Supplementary Material



Publikationsverlauf

Eingereicht: 18. Februar 2020

Angenommen: 10. Juli 2020

Artikel online veröffentlicht:
19. August 2020

© 2020. Thieme. All rights reserved.

Georg Thieme Verlag KG
Stuttgart · New York

 

  • References

  • 1 OMS | Maladies cardiovasculaires. WHO. Available at: http://www.who.int/entity/cardiovascular_diseases/fr/index.html . Accessed February 5, 2020
    PubMed
  • 2 Ninot G, Boulze Launay I, Bourrel G. , et al. From the definition of non-drug interventions to their ontology. Hegel 2018; 8 (01) 21-27
    PubMedGoogle Scholar
  • 3 Bobrow K, Farmer AJ, Springer D. , et al. Mobile phone text messages to support treatment adherence in adults with high blood pressure (SMS-text adherence support [StAR]): a single-blind, randomized trial. Circulation 2016; 133 (06) 592-600
    CrossrefPubMedGoogle Scholar
  • 4 Free C, Knight R, Robertson S. , et al. Smoking cessation support delivered via mobile phone text messaging (txt2stop): a single-blind, randomised trial. Lancet 2011; 378 (9785): 49-55
    CrossrefPubMedGoogle Scholar
  • 5 Berrouiguet S, Baca-García E, Brandt S, Walter M, Courtet P. Fundamentals for future mobile-health (mHealth): a systematic review of mobile phone and web-based text messaging in mental health. J Med Internet Res 2016; 18 (06) e135
    CrossrefPubMedGoogle Scholar
  • 6 Munn Z, Peters MDJ, Stern C, Tufanaru C, McArthur A, Aromataris E. Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach. BMC Med Res Methodol 2018; 18 (01) 143
    CrossrefPubMedGoogle Scholar
  • 7 Lamy J-B, Séroussi B, Griffon N, Kerdelhué G, Jaulent M-C, Bouaud J. Toward a formalization of the process to select IMIA Yearbook best papers. Methods Inf Med 2015; 54 (02) 135-144
    Artikel in Thieme ConnectPubMedGoogle Scholar
  • 8 Blixen C, Sajatovic M, Moore DJ. , et al. Patient participation in the development of a customized M-health intervention to improve medication adherence in poorly adherent individuals with bipolar disorder (BD) and hypertension (HTN). Int J Healthc 2018; 4 (01) 25-35
    CrossrefPubMedGoogle Scholar
  • 9 Buis LR, Dawood K, Kadri R. , et al. Improving blood pressure among african americans with hypertension using a mobile health approach (the MI-BP app): protocol for a randomized controlled trial. JMIR Res Protoc 2019; 8 (01) e12601
    CrossrefPubMedGoogle Scholar
  • 10 Burner E, Lam CN, DeRoss R, Kagawa-Singer M, Menchine M, Arora S. Using mobile health to improve social support for low-income latino patients with diabetes: a mixed-methods analysis of the feasibility trial of TExT-MED + FANS. Diabetes Technol Ther 2018; 20 (01) 39-48
    CrossrefPubMedGoogle Scholar
  • 11 Byrne JL, Dallosso HM, Rogers S. , et al. The ready to reduce risk (3R) study for a group educational intervention with telephone and text messaging support to improve medication adherence for the primary prevention of cardiovascular disease: protocol for a randomized controlled trial. JMIR Res Protoc 2018; 7 (11) e11289
    CrossrefPubMedGoogle Scholar
  • 12 Carrasquillo O, Young B, Dang S. , et al. Hispanic Secondary stroke prevention initiative design: study protocol and rationale for a randomized controlled trial. JMIR Res Protoc 2018; 7 (10) e11083
    CrossrefPubMedGoogle Scholar
  • 13 Cottrell MA, Hill AJ, O'Leary SP, Raymer ME, Russell TG. Patients are willing to use telehealth for the multidisciplinary management of chronic musculoskeletal conditions: a cross-sectional survey. J Telemed Telecare 2018; 24 (07) 445-452
    CrossrefPubMedGoogle Scholar
  • 14 Forsyth P, Richardson J, Lowrie R. Patient-reported barriers to medication adherence in heart failure in Scotland. Int J Pharm Pract 2019; 27 (05) 443-450
    CrossrefPubMedGoogle Scholar
  • 15 Fortuna KL, Aschbrenner KA, Lohman MC. , et al. Smartphone ownership, use, and willingness to use smartphones to provide peer-delivered services: results from a national online survey. Psychiatr Q 2018; 89 (04) 947-956
    CrossrefPubMedGoogle Scholar
  • 16 Gonzalez M, Sjölin I, Bäck M. , et al. Effect of a lifestyle-focused electronic patient support application for improving risk factor management, self-rated health, and prognosis in post-myocardial infarction patients: study protocol for a multi-center randomized controlled trial. Trials 2019; 20 (01) 76
    CrossrefPubMedGoogle Scholar
  • 17 Griffin N, Kehoe M. A questionnaire study to explore the views of people with multiple sclerosis of using smartphone technology for health care purposes. Disabil Rehabil 2018; 40 (12) 1434-1442
    CrossrefPubMedGoogle Scholar
  • 18 Holender A, Sutton S, De Simoni A. Opinions on the use of technology to improve tablet taking in >65-year-old patients on cardiovascular medications. J Int Med Res 2018; 46 (07) 2754-2768
    CrossrefPubMedGoogle Scholar
  • 19 Angellotti E, Wong JB, Pierce A, Hescott B, Pittas AG. Combining wireless technology and behavioral economics to engage patients (WiBEEP) with cardiometabolic disease: a pilot study. Pilot Feasibility Stud 2019; 5: 7
    CrossrefPubMedGoogle Scholar
  • 20 Korpershoek YJG, Vervoort SCJM, Trappenburg JCA, Schuurmans MJ. Perceptions of patients with chronic obstructive pulmonary disease and their health care providers towards using mHealth for self-management of exacerbations: a qualitative study. BMC Health Serv Res 2018; 18 (01) 757
    CrossrefPubMedGoogle Scholar
  • 21 Orchard J, Neubeck L, Freedman B. , et al. eHealth tools to provide structured assistance for atrial fibrillation screening, management, and guideline-recommended therapy in metropolitan general practice: the AF - SMART study. J Am Heart Assoc 2019; 8 (01) e010959
    CrossrefPubMedGoogle Scholar
  • 22 Recio-Rodríguez JI, Lugones-Sanchez C, Agudo-Conde C. , et al. Combined use of smartphone and smartband technology in the improvement of lifestyles in the adult population over 65 years: study protocol for a randomized clinical trial (EVIDENT-Age study). BMC Geriatr 2019; 19 (01) 19
    CrossrefPubMedGoogle Scholar
  • 23 Santo K, Hyun K, de Keizer L. , et al. The effects of a lifestyle-focused text-messaging intervention on adherence to dietary guideline recommendations in patients with coronary heart disease: an analysis of the TEXT ME study. Int J Behav Nutr Phys Act 2018; 15 (01) 45
    CrossrefPubMedGoogle Scholar
  • 24 Scott IA, Scuffham P, Gupta D, Harch TM, Borchi J, Richards B. Going digital: a narrative overview of the effects, quality and utility of mobile apps in chronic disease self-management. Aust Health Rev 2020; 44 (01) 62-82
    CrossrefPubMedGoogle Scholar
  • 25 Tang YH, Chong MC, Chua YP, Chui PL, Tang LY, Rahmat N. The effect of mobile messaging apps on cardiac patient knowledge of coronary artery disease risk factors and adherence to a healthy lifestyle. J Clin Nurs 2018; 27 (23-24): 4311-4320
    CrossrefPubMedGoogle Scholar
  • 26 Tran BX, Le XTT, Nguyen PN. , et al. Feasibility of e-health interventions on smoking cessation among Vietnamese active internet users. Int J Environ Res Public Health 2018; 15 (01) 165
    CrossrefPubMedGoogle Scholar
  • 27 Woringer M, Dharmayat KI, Greenfield G, Bottle A, Ray KK. American Heart Association's Cholesterol CarePlan as a smartphone-delivered web app for patients prescribed cholesterol-lowering medication: protocol for an observational feasibility study. JMIR Res Protoc 2019; 8 (01) e9017
    CrossrefPubMedGoogle Scholar
  • 28 Zullig LL, McCant F, Silberberg M, Johnson F, Granger BB, Bosworth HB. Changing CHANGE: adaptations of an evidence-based telehealth cardiovascular disease risk reduction intervention. Transl Behav Med 2018; 8 (02) 225-232
    CrossrefPubMedGoogle Scholar
  • 29 Wong EM, Chair SY, Leung DY, Sit JW, Leung KP. Home-based interactive e-health educational intervention for middle-aged adults to improve total exercise, adherence rate, exercise efficacy, and outcome: a randomised controlled trial. Hong Kong Med J 2018; 24 (01) (Suppl. 02) 34-38
    PubMedGoogle Scholar
  • 30 Salvi D, Ottaviano M, Muuraiskangas S. , et al. An m-Health system for education and motivation in cardiac rehabilitation: the experience of HeartCycle guided exercise. J Telemed Telecare 2018; 24 (04) 303-316
    CrossrefPubMedGoogle Scholar
  • 31 Gordon NP, Hornbrook MC. Older adults' readiness to engage with eHealth patient education and self-care resources: a cross-sectional survey. BMC Health Serv Res 2018; 18 (01) 220
    CrossrefPubMedGoogle Scholar
  • 32 Laranjo L, Arguel A, Neves AL. , et al. The influence of social networking sites on health behavior change: a systematic review and meta-analysis. J Am Med Inform Assoc 2015; 22 (01) 243-256
    CrossrefPubMedGoogle Scholar
  • 33 Meneton P, Lemogne C, Herquelot E. , et al. A global view of the relationships between the main behavioural and clinical cardiovascular risk factors in the GAZEL prospective cohort. PLoS One 2016; 11 (09) e0162386
    CrossrefPubMedGoogle Scholar
  • 34 Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol 2006; 3 (02) 77-101
    CrossrefPubMedGoogle Scholar
  • 35 Abraham C, Michie S. A taxonomy of behavior change techniques used in interventions. Health Psychol 2008; 27 (03) 379-387
    CrossrefPubMedGoogle Scholar
  • 36 Cortet B, Bénichou O. Adherence, persistence, concordance: do we provide optimal management to our patients with osteoporosis?. Joint Bone Spine 2006; 73 (05) e1-e7
    CrossrefPubMedGoogle Scholar
  • 37 Barbosa CD, Balp M-M, Kulich K, Germain N, Rofail D. A literature review to explore the link between treatment satisfaction and adherence, compliance, and persistence. Patient Prefer Adherence 2012; 6: 39-48
    CrossrefPubMedGoogle Scholar
  • 38 Badawy SM, Barrera L, Sinno MG, Kaviany S, O'Dwyer LC, Kuhns LM. Text messaging and mobile phone apps as interventions to improve adherence in adolescents with chronic health conditions: a systematic review. JMIR Mhealth Uhealth 2017; 5 (05) e66
    CrossrefPubMedGoogle Scholar
  • 39 Ugon A, Hadj Bouzid AI, Jaulent M-C. , et al. Building a knowledge-based tool for auto-assessing the cardiovascular risk. Stud Health Technol Inform 2018; 247: 735-739
    PubMedGoogle Scholar
  • 40 Carbonnel F, Ninot G. Identifying frameworks for validation and monitoring of consensual behavioral intervention technologies: narrative review. J Med Internet Res 2019; 21 (10) e13606
    CrossrefPubMedGoogle Scholar