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Yearb Med Inform 2013; 22(01): 162-168
DOI: 10.1055/s-0038-1638849
Original Article
Georg Thieme Verlag KG Stuttgart

Social Media for the Promotion of Holistic Self-Participatory Care: An Evidence Based Approach

Contribution of the IMIA Social Media Working Group
T. Miron-Shatz
1   Center for Medical Decision Making, Ono Academic College, Israel
2   Center for Medicine in the Public Interest, New York, NY, USA
,
M. M. Hansen
3   School of Nursing and Health Professions, University of San Francisco, San Francisco, CA, USA
,
F. J. Grajales III
4   eHealth Strategy Office, The University of British Columbia, Vancouver, BC, Canada
,
F. Martin-Sanchez
5   Health and Biomedical Informatics Research Unit, Medical School, The University of Melbourne, Melbourne, Australia
,
P. D. Bamidis
6   Lab of Medical Informatics, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece
› Author Affiliations
Further Information

Publication History

Publication Date:
05 March 2018 (online)

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Summary

Objectives: As health information is becoming increasingly accessible, social media offers ample opportunities to track, be informed, share and promote health. These authors explore how social media and holistic care may work together; more specifically however, our objective is to document, from different perspectives, how social networks have impacted, supported and helped sustain holistic self-participatory care.

Methods: A literature review was performed to investigate the use of social media for promoting health in general and complementary alternative care. We also explore a case study of an intervention for improving the health of Greek senior citizens through digital and other means.

Results: The Health Belief Model provides a framework for assessing the benefits of social media interventions in promoting comprehensive participatory self-care. Some interventions are particularly effective when integrating social media with real-world encounters. Yet not all social media tools are evidence-based and efficacious. Interestingly, social media is also used to elicit patient ratings of treatments (e.g., for depression), often demonstrating the effectiveness of complementary treatments, such as yoga and mindfulness meditation.

Conclusions: To facilitate the use of social media for the promotion of complementary alternative medicine through self-quantification, social connectedness and sharing of experiences, exploration of concrete and abstract ideas are presented here within. The main mechanisms by which social support may help improve health – emotional support, an ability to share experiences, and non-hierarchal roles, emphasizing reciprocity in giving and receiving support – are integral to social media and provide great hope for its effective use.

Keywords

web 2.0 - evidence-based health care - community-based participatory research - holistic health - self-management
 

  • References

  • 1 Fox S, Duggan M. Pew Internet Health Online 2013, Summary of Findings. [cited February 2013] Available from: http://www.pewinter-net.org/reports/2013/Health-online?Summary-of-Findings.aspx
    PubMedGoogle Scholar
  • 2 Crawford M. Empowered patients are here to stay. Health Prog 2012; Mar-Apr 93 (2) 18-23.
    PubMedGoogle Scholar
  • 3 Swan M. Emerging patient-driven health care models: an examination ofhealth social networks, consumer personalized medicine and quantified self-tracking. Int J Environ Res Public Health 2009; Feb 6 (2) 492-525.
    CrossrefPubMedGoogle Scholar
  • 4 Swan M. Crowdsourced health research studies: an important emerging complement to clinical trials in the public health research ecosystem. J Med Internet Res 2012; Mar 7 14 (2) e46.
    CrossrefPubMedGoogle Scholar
  • 5 National Center for Complementary and Alternative Medicine (NCCAM) [Internet]. Bethesda, MD: NCCAM; 2008. Oct [updated 2011 Jul; cited 2012 Dec 21] CAM Basics: What is Complementary and Alternative Medicine?. [about 7 screens] Available from: http://nccam.nih.gov/health/whatiscam
    Google Scholar
  • 6 Killen Jr. J. Our center's niche at NIH. 2012 Oct 30 [cited 2012 Dec 19]. In: NCCAM Research Blog [Internet]. Available from http://nccam.nih.gov/research/blog/niche
    PubMedGoogle Scholar
  • 7 Hazelwood G. 12 Yoga apps to become a better yogi. 2012 [cited 2012 Dec 19] In: Greatist: Choose Better [Internet]. Available from: http://greatist.com/fitness/yoga-mobile-apps/
    PubMedGoogle Scholar
  • 8 Selhub EM, Logan AC. Your brain on nature: the science of nature's influence on your health, happiness and vitality. Mississauga, ON, Canada: John Wiley & Sons; 2012
    Google Scholar
  • 9 Hansen MM. The effects of complementary therapies delivered via mobile technologies on surgical patients' reports of anxiety, pain and self-efficacy in healing: a randomized controlled trial [Internet]. Presented at: Medicine X 2012. 2012. Sep 28-30 Stanford, CA: [cited 2012 Dec 22] Available from: http://medicinex.stanford.edu/conferences/index.php/medx/2012/paper/view/29
    Google Scholar
  • 10 Walsh T. Integrative options prevail in social patient bipolar research. 2012 Jun 19 [cited 2012 Dec 19] In: Integrative Health and Wellness Strategies [Internet]. Available from: http://www.integra-tivestrategies.us/?p=461
    PubMedGoogle Scholar
  • 11 Carmichael A. Matt Keener on the brain and self-quantification: a bidirectional relationship. 2012 Sep 8 [cited 2012 Dec 19] In: Quantified Self: Self Knowledge Through Numbers [Internet]. Available from: http://quantified-self.com/2012/09/matt-keener-on-the-brain/
    PubMedGoogle Scholar
  • 12 Cure Together. Infographic: 40 biploar disorder treatments compared [Internet]. 2012 [cited 2012 Nov 25] Available from: http://curetogether.com/bipolar-disorder/ig/treatment-effectiveness-vs-popularity
    PubMedGoogle Scholar
  • 13 Rosenstock IM. Why people use health services. Milbank Mem Fund Q 1966; 44 Suppl 3 94-127.
    CrossrefPubMedGoogle Scholar
  • 14 Glantz K, Rimer BK, Viswanath K. editors. Health behavior and health education. San Francisco: John Wiley & Sons; 2008
  • 15 Conner M, Norman P. editors. Predicting health behavior: search and practice with social cognition models. 2nd ed. Berkshire, UK: Open University Press; 1996
  • 16 Poortinga W. Social relations or social capital? Individual and community health effects of bonding social capital. Soc Sci Med 2006; Jul 63 (1) 255-70.
    CrossrefPubMedGoogle Scholar
  • 17 Uchino BN, Caccioppo JT, Kiecolt-Glaser JK. The relationship between social support and physiological processes: a review with emphasis on underlying mechanisms and implications for health. Psychol Bull 1996; 119 (3) 488-531.
    CrossrefPubMedGoogle Scholar
  • 18 Uchino BN. Social support and health: a review of physiological processes potentially underlying links to disease outcomes. J Behav Med 2006; Aug: 29 (4) 377-87.
    CrossrefPubMedGoogle Scholar
  • 19 Cohen S. Psychosocial models ofthe role ofsocial support in the etiology of physical disease. Health Psychol 1988; 7 (3) 269-97.
    CrossrefPubMedGoogle Scholar
  • 20 DiMatteo MR. Social support and patient adherence to medical treatment: a meta-analysis. Health Psy 2004; Mar 23 (2) 207-18.
    PubMedGoogle Scholar
  • 21 Heisler M, Vijan S, Makki F, Piette JD. Diabetes control with reciprocal peer support versus nurse care management: a randomized trial. Ann Intern Med 2010; Oct 19 153 (8) 507-15.
    CrossrefPubMedGoogle Scholar
  • 22 Prochaska JJ, Pechmann C, Kim R, Leonhardt JM. Twitter = quitter? An analysis of Twitter quit smoking social networks. Tob Control 2012; Jul 21 (4) 447-9.
    CrossrefPubMedGoogle Scholar
  • 23 Wills TA, Yaeger AM. Family factors and adolescent substance use: models and mechanisms. Curr Dir Psychol Sci 2003; Dec 12 (6) 222-6.
    CrossrefPubMedGoogle Scholar
  • 24 Stephanidis C. Ambient assisted living and ambient intelligence: improving the quality of life for european citizens. ERCIM News 2011; Oct 87: 2-3.
    PubMedGoogle Scholar
  • 25 Braam AW, Beekman AT, Dewey ME, Delespaul PA, Fichter M, Lobo A. et al. Depression and parkinsonism in older Europeans: results from the EURODEP concerted action. Int J Geriatr Psychiatry 2010; Jul 25 (7) 679-87.
    PubMedGoogle Scholar
  • 26 Strohle A. Physical activity, exercise, depression and anxiety disorders. J Neural Transm 2009; Jun 116 (6) 777-84.
    CrossrefPubMedGoogle Scholar
  • 27 Konstantinidis EI, Billis A, Grigoriadou E, Sidiropoulos S, Fasnaki S, Bamidis PD. Affective computing on elderly physical and cognitive training within live social networks. In: Maglogiannis I, Plagianakos V, Vlahavas I. editors. SETN'12 Proceedings of the 7th Hellenic conference on artificial intelligence: theories and applications; 2012. May 28-30 Lamia, Greece. Berlin: Springer; 2012. p. 339-44.
    Google Scholar
  • 28 Laurin D, Verreault R, Lindsay J, MacPherson K, Rockwood K. Physical activity and risk of cognitive impairment and dementia in elderly persons. Arch Neurol 2001; Mar 58 (3) 498-504.
    PubMedGoogle Scholar
  • 29 Mowszowski L, Batchelor J, Naismith SL. Early intervention for cognitive decline: can cognitive training be used as a selective prevention technique?. Int Psychogeriatr 2010; Jun 22 (4) 537-48.
    CrossrefPubMedGoogle Scholar
  • 30 Bamidis PD, Konstantinidis EI, Billis A, Frantzidis C, Tsolaki M, Hlauschek W. et al. A Web services-based exergaming platform for senior citizens: the Long Lasting Memories project approach to e-health care. In: Proceedings ofthe 33rd Annual International Conference of IEEE EMBS; 2011. Aug 30-Sep 3 Boston, MA: Conf Proc IEEE Eng Med Biol Soc; 2011. 2011 2505-9.
    Google Scholar
  • 31 Smith GE, Housen P, Yaffe K, Ruff R, Kennison RF, Mahncke HW. et al. A cognitive training program based on principles of brain plasticity: results from the Improvement in Memory with Plasticity-based Adaptive Cognitive Training (IMPACT) study. J Am Geriatr Soc 2009; Apr 57 (4) 594-603.
    CrossrefPubMedGoogle Scholar
  • 32 Billis AS, Konstantinidis EI, Ladas AI, Tsolaki MN, Pappas C, Bamidis PD. Evaluating affective usability experiences of an exergaming platform for seniors. In: Proceedings ofthe 10th International Workshop on Biomedical Engineering; 2011 Oct 5-7. Kos, Greece: IEEE; 2011
    Google Scholar
  • 33 Tsapanou A, Margioti L, Beratis I, Papatriantafyllou J, Kamtsadeli V, Nika A. et al. Cognitive and physical training for the prevention of cognitive decline in the elderly: preliminary data of the Long Lasting Memories European project. Neurosci Lett Suppl 2011; Jul 500: e5-6.
    PubMedGoogle Scholar
  • 34 Bamidis P, Frantzidis C, Kyrillidou A, Ladas A, Grigoriadou E, Billis A. et al. Cognitive training, physical exercise and information technology: neu-roscientific challenges and first evidence from the LLM project. Neurosci Lett Suppl. 2011 Jul 500. e6.
    PubMedGoogle Scholar
  • 35 Bamidis PD. Long lasting memories (LLM): a unified solution for cognitive and physical health and autonomous living for senior citizens. 2012 Nov 27 [cited 2012 Dec 20] In: Long-Lasting Memories: Mind and Body Fitness for Life [Internet]. Available from: http://www.longlastingmemories.eu
    PubMedGoogle Scholar
  • 36 Bratsas C, Kapsas G, Konstantinidis S, Koutsouridis G, Bamidis P. A semantic wiki within moodle for Greek medical education. In: Proceedings of the 22nd IEEE International Symposium on Computer-Based Medical Systems (CBMS). 2009. Aug 2-5 Albuquerque, NM: IEEE; 2009.
    Google Scholar
  • 37 Semantic MediaWiki (SMW) [Internet]. Karlsruhe, Germany: Karlsruhe Institute of Technology. 2007 [cited 2012 Dec 21]. Available from: http://semantic-mediawiki.org
    PubMedGoogle Scholar
  • 38 Kontotasiou D, Bratsas C, Bamidis PD. Modeling medical interventions using the semantic Media Wiki for use in healthcare practice and education. In: Proceedings of the 24th International Symposium on Computer-Based Medical Systems (CBMS), 2011. Jun 27-30 Bristol, UK: IEEE; 2011
    Google Scholar
  • 39 Bizer C, Heath T, Berners-Lee T. Linked data — the story so far. Int J Semantic Web Inf Syst 2009; Mar 5 (3) 1-22.
    PubMedGoogle Scholar
  • 40 Bamidis P, Kaldoudi E, Pattichis C. mEducator: a best practice network for repurposing and sharing medical educational multi-type content. In: Camarinha-Matos LM, Paraskakis I, Afsarmanesh H. editors. Leveraging knowledge for innovation in collaborative networks. Proceedings of the 10th IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE, 2009. Oct 7-9 Thessaloniki, Greece: IFIP Advances in Information and Communication Technology; Vol. 307 Berlin: Springer; 2009. p. 769-76.
    Google Scholar
  • 41 Paton C, Bamidis PD, Eysenbach G, Hansen M, Cabrer M. Experience in the use of social media in medical and health education. Contribution of the IMIA Social Media Working Group. Yearb Med Inform 2011; 6 (1) 21-9.
    Article in Thieme ConnectPubMedGoogle Scholar
  • 42 Konstantinidis S, Luque L, Bamidis P, Karlsen R. The Role of Taxonomies in Social Media and the Semantic Web for Health Education A Study of SNOMED CT Terms in YouTube Health Video Tags. Methods Inf Med 2013; 52 (2) 168-79.
    Article in Thieme ConnectPubMedGoogle Scholar
  • 43 Sackett D, Rosenberg WM, Gray JA, Haynes RB, Smith R. Evidence based medicine: what it is and what it isn't. BMJ 1996; 312 (7023) 71-2.
    CrossrefPubMedGoogle Scholar
  • 44 Wicks P, Vaughan TW, Massagli MP, Heywood J. Accelerated clinical discovery using self-reported patient data collected online and a patient-matching algorithm. Nat Biotechnol 2011; May 29 (5) 411-4.
    CrossrefPubMedGoogle Scholar
  • 45 Jadad AR, Enkin MW. Randomized controlled trials: questions, answers and musings. 2nd ed. Malden, MA: Blackwell; 2007
    Google Scholar
  • 46 Frydman GJ. Patient-driven research: rich opportunities and real risks. J Participat Med 2009; Oct 1 (1) e12.
    PubMedGoogle Scholar
  • 47 Mayo Clinic Center for Social Media. Bringing the Social Media Revolution to Health Care. 2012. Mayo Foundation for Medical Education.;
    Google Scholar