Yearb Med Inform 2011; 20(01): 131-138
DOI: 10.1055/s-0038-1638751
Working Group Contributions
Georg Thieme Verlag KG Stuttgart

The Role of Social Media for Patients and Consumer Health

Contribution of the IMIA Consumer Health Informatics Working Group
A. Y. S. Lau
1   Centre for Health Informatics, Australian Institute of Health Innovation, University of New South Wales, Sydney, Australia
,
K. A. Siek
2   Wellness Innovation and Interaction Laboratory, University of Colorado at Boulder, Department of Computer Science, Boulder, USA
,
L. Fernandez-Luque
3   Northern Research Institute, Tromsø, Norway
,
H. Tange
4   Caphri School of Public Health and Primary Care, Maastricht University, The Netherlands
,
P. Chhanabhai
5   Department of Information Science, University of Otago, New Zealand
,
S. Y. W. Li
6   Department of Sociology and Social Policy, Lingnan University, Hong Kong
,
P. L. Elkin
7   Department of Internal Medicine Director, Center for Biomedical Informatics Mount Sinai School of Medicine, New York, USA
,
A. Arjabi
8   School of Engineering and Digital Arts, University of Kent, Canterbury, UK
,
L. Walczowski
8   School of Engineering and Digital Arts, University of Kent, Canterbury, UK
,
C. S. Ang
8   School of Engineering and Digital Arts, University of Kent, Canterbury, UK
,
G. Eysenbach
9   Centre for global eHealth Innovation, University Health Network, Toronto, Canada
10   Department of Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canada
› Institutsangaben
Weitere Informationen

Correspondence to

Annie Lau
Centre for Health Informatics
Australian Institute of Health Innovation
University of New South Wales
Sydney, Australia
Telefon: +61(2) 9385 8891   
Fax: +61(2) 9385 8692   

Publikationsverlauf

Publikationsdatum:
06. März 2018 (online)

 

Summary

Objectives

To provide an overview on social media for consumers and patients in areas of health behaviours and outcomes.

Methods

A directed review of recent literature.

Results

We discuss the limitations and challenges of social media, ranging from social network sites (SNSs), computer games, mobile applications, to online videos. An overview of current users of social media (Generation Y), and potential users (such as low socioeconomic status and the chronically ill populations) is also presented. Future directions in social media research are also discussed.

Conclusions

We encouragethe health informaticscommunity to consider the socioeconomic class, age, culture, and literacy level of their populations, and select an appropriate medium and platform when designing social networkedinterventionsforhealth.Little isknown about the impact of second-hand experiences faciliated by social media, nor the quality and safety of social networks on health. Methodologies and theories from human computer interaction, human factors engineering and psychology may help guide the challenges in design-ingand evaluatingsocial networkedinterventionsforhealth. Further, by analysing how people search and navigate social media for health purposes, infodemiology and infoveillance are promising areas of research that should provide valuable insights on present and emergening health behaviours on a population scale.


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Correspondence to

Annie Lau
Centre for Health Informatics
Australian Institute of Health Innovation
University of New South Wales
Sydney, Australia
Telefon: +61(2) 9385 8891   
Fax: +61(2) 9385 8692   

  • References

  • 1 Bodenheimer T, Lorig K, Holman H, Grumbach K. Patient self-management of chronic disease in primary care. JAMA 2002; 288 (19) 2469-75.
  • 2 Rogers EM. Diffusion of Innovations. 4th ed. New York, NY: The Free Press; 1995
  • 3 Jones S. PEW internet project data memo. Pew internet &American life project. 2009 [11Apr 2011]; Available from: http://www.pewinternet.org/media//Files/Reports/2009/PIP_Generations_2009.pdf
  • 4 Lieberman MA, Golant M, Giese-Davis J, Winzlenberg A, Benjamin H, Humphreys K. et al. Electronic support groups for breast carcinoma: A clinical trial of effectiveness. Cancer 2003; 97 (04) 920-5.
  • 5 Lorig KR, Laurent DD, Deyo RA, Marnell ME, Minor MA, Ritter PL. Can a Back Pain E-mail Discussion Group improve health status and lower health care costs?: A randomized study. Arch Intern Med 2002; 167 (07) 792-6.
  • 6 Dawes M, Sampson U. Knowledge management in clinical practice:A systematic review of information seeking behavior in physicians. Int J Med Inform 2003; 71 (01) 9-15.
  • 7 Coumou HCH, Meijman FJ. How do primary care physicians seek answers to clinical questions? A literature review. J Med Libr Assoc 2006; 94 (01) 55-6.
  • 8 Shaw BR, McTavish F, Hawkins R, Gustafson DH, Pingree S. Experiences of women with breast cancer: Exchanging social support over the chess computer network. J Health Commun 2000; 05 (02) 135-59.
  • 9 McGettigan P, Golden J, Fryer J, Chan R, Feely J. The sources of information used by doctors for prescribing suggest that the medium is more important than the message. Br J Clin Pharmacol 2001; 51 (02) 184-9.
  • 10 Berkman L, Glass T. Social integration, social networks, social support and health. In: Berkman L, Kawachi I. editors. Social epidemiology. New York: Oxford University Press; 2000
  • 11 Latané B. The psychology of social impact. Am Psychol 1981; 36 (04) 343-56.
  • 12 Amichai-Hamburger Y, McKenna KYA. The Contact Hypothesis Reconsidered: Interacting via the Internet. J Comput Mediat Commun 2006; 11: 825-43.
  • 13 Pirolli P. An Elementary Social Information Foraging Model. Computer Human Interaction Conference (CHI 2009). Boston, MA: 2009
  • 14 Fowler JH, Christakis NA. Dynamic spread of happiness in a large social network: longitudinal analysis over 20 years in the Framingham Heart Study. BMJ 2008; 337: a2338.
  • 15 Smith KP, Christakis NA. Social Networks and Health. Annu Rev Sociol 2008; 34: 405-29.
  • 16 Lau AYS, Coiera EW. Impact of Web Searching and Social Feedback on Consumer Decision Making: A Prospective Online Experiment. J Med Internet Res 2008; 10 (01) e2.
  • 17 Lau AYS, Kwok TMY. Social features in online communities for healthcare consumers - a review. Online Communities and Social Computing: Third International Conference, OCSC 2009, Held as Part of HCI International 2009, San Diego, CA, USA, July 19-24, 2009, Proceedings LNCS 5621. Berlin Heidelberg: Springer-Verlag; 2009: 682-9.
  • 18 Lau AYS, Kwok T, Coiera E. The Influence of Crowds on Consumer Health Decisions: An Online Prospective Study 13th World Congress on Medical and Health Informatics (MedInfo 2010). 2010. Cape Town, South Africa: MedInfo.;
  • 19 Yang CT, Tang X. Who Made the Most Influence in MedHelp?. IEEE Intelligent Systems, 13 Sept 2010 IEEE computer Society Digital Library IEEE Computer Society. 2010
  • 20 Jones JHS, Salathé M. Early assessment of anxiety and behavioral response to novel swine-origin influenza A(H1N1). PLoS ONE 2009; 04: e8032.
  • 21 PatientsLikeMe. 2011 [14Apr 2011];Available from: http://www.patientslikeme.com/
  • 22 Frost J, Massagli MP. Social Uses of Personal Health Information Within PatientsLikeMe, an Online Patient Community: What Can Happen When Patients Have Access to One Another’s Data. J Med Internet Res 2008; May 27; 10 (03) e15.
  • 23 Wicks P, Massagli M, Frost J, Brownstein C, Okun S, Vaughan T, Bradley R, Heywood J. Sharing Health Data for Better Outcomes on PatientsLikeMe. J Med Internet Res. 2010 12. 2 e19
  • 24 Frost J, Okun S, Vaughan T, Heywood J, Wicks P. Patient-reported outcomes as a source of evidence in off-label prescribing: analysis of data from PatientsLikeMe. J Med Internet Res 2011; 13 (01) e6.
  • 25 Huss K, Winkelstein M, Nanda J, Naumann PL, Sloand ED, Huss RW. Computer game for innercity children does not improve asthma outcomes. J Pediatr Health Care 2003; 17 (02) 72-8.
  • 26 Yoon SL, Godwin A. Enhancing self-management in children with sickle cell disease through playing a CD-ROM educational game: a pilot study. Pediatr Nurs 2007; 33 (01) 60-372.
  • 27 Beale IL, Kato PM, Marin-Bowling VM, Guthrie N, Cole SW. Improvement in cancer-related knowledge following use of a psychoeducational video game for adolescents and young adults with cancer. J Adolesc Health 2007; Sep; 41 (03) 263-70.
  • 28 Brown SJ, Lieberman DA, Germeny BA, Fan YC, Wilson DM, Pasta DJ. Educational video game for juvenile diabetes: results of a controlled trial. Med Infor (Lond) 1997; 22 (01) 77-89.
  • 29 Shilts MK, Horowitz M, Townsend MS. Goal setting as a strategy for dietary and physical-activity behavior change: a review of the literature. Am J Health Promotion 2004; 19: 81-93.
  • 30 deVries H, Brug J. Computer-tailored interventions motivating people to adopt health promoting behaviours: introduction to a new approach. Patient Educ Couns 1999; Feb; 36 (02) 99-105.
  • 31 Second Life. [2 Feb 2011]; Available from: secondlife.com.
  • 32 Bandura A. Self-efficacy: the exercise of control. NewYork: Freeman; 1997
  • 33 Roomi J, Johnson MM, Waters K, Yohannes A, Helm ACMJ. Respiratory rehabilitation, exercise capacity and quality of life in chronic airways disease in old age. Age Ageing 1996; 25 (01) 12-6.
  • 34 Tauer JM, Harackiewicz JM. The effects of cooperation and competition on intrinsic motivation and performance. Personal Soc Psycho 2004; 86: 849-61.
  • 35 Graves L, Stratton G, Ridgers ND, Cable NT. Energy expenditure in adolescents playing new generation computer games. Br J Sports Med 2008; Jul; 42 (07) 592-4.
  • 36 Lanningham-Foster L, Jensen TB, Foster RC, Redmond AB, Walker BA, Heinz D. et al. Energy expenditure of sedentary screen time compared with active screen time for children. Pediatrics 2006; Dec; 118 (06) e1831-5.
  • 37 Murphy EC, Carson L, Neal W, Baylis C, Donley D, Yeater R. Effects of an exercise intervention using Dance Dance Revolution on endothelial function and other risk factors in overweight children. Int J Pediatr Obes 2009; 04 (04) 205-14.
  • 38 Games for Health. 2011 [17 May 2011]; Available from: http://www.gamesforhealth.org/
  • 39 Madan A, Moturu S, Lazer D, Pentland A. Social Sensing: Obesity, unhealthy Eating and Exercise in Face-to-face Networks. proceedings: UbiComp ‘10, Sep 26-9, 2010. Copenhagen, Denmark ACM: ACM.;
  • 40 Consolvo S, Klasnja P, McDonald DW, Avrahami D, Froehlich J, LeGrand L. et al. Flowers or a robot army?: encouraging awareness & activity with personal, mobile displays. Proceedings of the 10th international conference on Ubiquitous computing. Seoul, Korea. 1409644: ACM; 2008: 54-63.
  • 41 Fujiki Y, Kazakos K, Puri C, Buddharaju P, Pavlidis I, Levine J. Neat-o-games: blending physical activity and fun in the daily routine. Comput Entertain 2008; 1-22.
  • 42 Oliveira RD, Cherubini M, Oliver N. MoviPill: improving medication compliance for elders using a mobile persuasive social game. Proceedings: UbiComp ‘10, Sep 26-Sep 29, 2010. Copenhagen, Denmark: ACM.;
  • 43 Lin J, Mamykina L, Lindtner S, Delajoux G, Strub H. Fish’n’Steps: Encouraging Physical Activity with an Interactive Computer Game. In: Dourish P, Friday A. editors. UbiComp 2006: Ubiquitous Computing. Springer; Berlin / Heidelberg: 2006: 261-78.
  • 44 Frost JH, Massagli MP, Wicks P, Heywood J. How the Social Web Supports patient experimentation with a new therapy: The demand for patient-controlled and patient-centered informatics. AMIA Annu Symp Proc 2008; 217-21.
  • 45 Mechael P, Batavia H, Kaonga N, Searle S, Kwan A, Goldberger A. et al. Barriers and Gaps Affecting mHealth in Low and Middle Income Countries: Policy White Paper: The Earth Institute Columba University. 2010
  • 46 Madden M. Online Video. 2007 July 25, 2007 [17 May 2011]; Available from: http://www. pewinternet.org/∼/media//Files/Reports/2007/PIP_Online_Video_2007.pdf.pdf
  • 47 Armstrong AWKR, Idriss NZ, Larsen LN, Lio PA. Online video improves clinical outcomes in adults with atopic dermatitis: a randomized controlled trial. J Am Acad Dermatol 2011; 64 (03) 502-7.
  • 48 Geller MA, Downs LS, Judson PL, Ghebre R, Argenta PA, Carson LF. et al. Learning about ovarian cancer at the time of diagnosis: Video versus usual care. Gynecol Oncol [doi: DOI: 10.1016/ j.ygyno.2010.06.032] 2010; 119 (02) 370-5.
  • 49 CDC. CDC-Online Video: CDC-TV anYouTube - eHealth Metrics Dashboard. 2010 Available from: http://www.cdc.gov/metrics/socialmedia/online- video.html
  • 50 CDC. YouTube and Online Video Guidelines and Best Practices. 2010 [17 May 2011];Available from. http://www.cdc.gov/SocialMedia/Tools/guidelines/pdf/onlinevideo.pdf
  • 51 Ache KA, Wallace LS. Human papillomavirus vaccination coverage on YouTube. Am J Prev Med 2008; Oct; 35 (04) 389-92.
  • 52 Elkin L, Thomson G, Wilson N. Connecting world youth with tobacco brands:YouTube and the internet policy vacuum on Web 2.0. Tob Control 2010; Oct; 19 (05) 361-6.
  • 53 Hussin M, Frazier S, Thompson JK. Fat stigmatization onYouTube: a content analysis. Body Image 2011; Jan; 08 (01) 90-2.
  • 54 Chou WY, Hunt Y, Folkers A, Augustson E. Cancer Survivorship in the Age of YouTube and Social Media: A Narrative Analysis. J Med Internet Res 2011; 13 (01) e7.
  • 55 Fernandez-Luque L, Elahi N, Grajales 3rd FJ. An analysis of personal medical information disclosed inYouTube videos created by patients with multiple sclerosis. Stud Health Technol Inform 2009; 150: 292-6.
  • 56 Fox S, Jones S. The social life of health information2009. Available from: http:// www.pewinternet.org/Reports/2009/8-The-Social-Life-of-Health-Information.aspx
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