Are health behavior change interventions that use online social networks effective? A systematic review

Carol A Maher, Lucy K Lewis, Katia Ferrar, Simon Marshall, Ilse De Bourdeaudhuij, Corneel Vandelanotte, Carol A Maher, Lucy K Lewis, Katia Ferrar, Simon Marshall, Ilse De Bourdeaudhuij, Corneel Vandelanotte

Abstract

Background: The dramatic growth of Web 2.0 technologies and online social networks offers immense potential for the delivery of health behavior change campaigns. However, it is currently unclear how online social networks may best be harnessed to achieve health behavior change.

Objective: The intent of the study was to systematically review the current level of evidence regarding the effectiveness of online social network health behavior interventions.

Methods: Eight databases (Scopus, CINAHL, Medline, ProQuest, EMBASE, PsycINFO, Cochrane, Web of Science and Communication & Mass Media Complete) were searched from 2000 to present using a comprehensive search strategy. Study eligibility criteria were based on the PICOS format, where "population" included child or adult populations, including healthy and disease populations; "intervention" involved behavior change interventions targeting key modifiable health behaviors (tobacco and alcohol consumption, dietary intake, physical activity, and sedentary behavior) delivered either wholly or in part using online social networks; "comparator" was either a control group or within subject in the case of pre-post study designs; "outcomes" included health behavior change and closely related variables (such as theorized mediators of health behavior change, eg, self-efficacy); and "study design" included experimental studies reported in full-length peer-reviewed sources. Reports of intervention effectiveness were summarized and effect sizes (Cohen's d and 95% confidence intervals) were calculated wherever possible. Attrition (percentage of people who completed the study), engagement (actual usage), and fidelity (actual usage/intended usage) with the social networking component of the interventions were scrutinized.

Results: A total of 2040 studies were identified from the database searches following removal of duplicates, of which 10 met inclusion criteria. The studies involved a total of 113,988 participants (ranging from n=10 to n=107,907). Interventions included commercial online health social network websites (n=2), research health social network websites (n=3), and multi-component interventions delivered in part via pre-existing popular online social network websites (Facebook n=4 and Twitter n=1). Nine of the 10 included studies reported significant improvements in some aspect of health behavior change or outcomes related to behavior change. Effect sizes for behavior change ranged widely from -0.05 (95% CI 0.45-0.35) to 0.84 (95% CI 0.49-1.19), but in general were small in magnitude and statistically non-significant. Participant attrition ranged from 0-84%. Engagement and fidelity were relatively low, with most studies achieving 5-15% fidelity (with one exception, which achieved 105% fidelity).

Conclusions: To date there is very modest evidence that interventions incorporating online social networks may be effective; however, this field of research is in its infancy. Further research is needed to determine how to maximize retention and engagement, whether behavior change can be sustained in the longer term, and to determine how to exploit online social networks to achieve mass dissemination. Specific recommendations for future research are provided.

Keywords: Internet; behavior change; intervention; physical activity; social network; systematic review; weight loss.

Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
Flow of studies through the review.
Figure 2
Figure 2
Forest plot of effect sizes for behavior change, downstream, and mediator variables.

References

    1. Scarborough P, Bhatnagar P, Wickramasinghe KK, Allender S, Foster C, Rayner M. The economic burden of ill health due to diet, physical inactivity, smoking, alcohol and obesity in the UK: an update to 2006-07 NHS costs. J Public Health (Oxf) 2011;33(4):527–35. doi: 10.1093/pubmed/fdr033.
    1. Narayan KM, Ali MK, Koplan JP. Global noncommunicable diseases--where worlds meet. N Engl J Med. 2010;363(13):1196–8. doi: 10.1056/NEJMp1002024.
    1. Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, Amann M, Anderson HR, Andrews KG, Aryee M, Atkinson C, Bacchus LJ, Bahalim AN, Balakrishnan K, Balmes J, Barker-Collo S, Baxter A, Bell ML, Blore JD, Blyth F, Bonner C, Borges G, Bourne R, Boussinesq M, Brauer M, Brooks P, Bruce NG, Brunekreef B, Bryan-Hancock C, Bucello C, Buchbinder R, Bull F, Burnett RT, Byers TE, Calabria B, Carapetis J, Carnahan E, Chafe Z, Charlson F, Chen H, Chen JS, Cheng AT, Child JC, Cohen A, Colson KE, Cowie BC, Darby S, Darling S, Davis A, Degenhardt L, Dentener F, Des Jarlais DC, Devries K, Dherani M, Ding EL, Dorsey ER, Driscoll T, Edmond K, Ali SE, Engell RE, Erwin PJ, Fahimi S, Falder G, Farzadfar F, Ferrari A, Finucane MM, Flaxman S, Fowkes FG, Freedman G, Freeman MK, Gakidou E, Ghosh S, Giovannucci E, Gmel G, Graham K, Grainger R, Grant B, Gunnell D, Gutierrez HR, Hall W, Hoek HW, Hogan A, Hosgood HD, Hoy D, Hu H, Hubbell BJ, Hutchings SJ, Ibeanusi SE, Jacklyn GL, Jasrasaria R, Jonas JB, Kan H, Kanis JA, Kassebaum N, Kawakami N, Khang YH, Khatibzadeh S, Khoo JP, Kok C, Laden F, Lalloo R, Lan Q, Lathlean T, Leasher JL, Leigh J, Li Y, Lin JK, Lipshultz SE, London S, Lozano R, Lu Y, Mak J, Malekzadeh R, Mallinger L, Marcenes W, March L, Marks R, Martin R, McGale P, McGrath J, Mehta S, Mensah GA, Merriman TR, Micha R, Michaud C, Mishra V, Mohd Hanafiah K, Mokdad AA, Morawska L, Mozaffarian D, Murphy T, Naghavi M, Neal B, Nelson PK, Nolla JM, Norman R, Olives C, Omer SB, Orchard J, Osborne R, Ostro B, Page A, Pandey KD, Parry CD, Passmore E, Patra J, Pearce N, Pelizzari PM, Petzold M, Phillips MR, Pope D, Pope CA, Powles J, Rao M, Razavi H, Rehfuess EA, Rehm JT, Ritz B, Rivara FP, Roberts T, Robinson C, Rodriguez-Portales JA, Romieu I, Room R, Rosenfeld LC, Roy A, Rushton L, Salomon JA, Sampson U, Sanchez-Riera L, Sanman E, Sapkota A, Seedat S, Shi P, Shield K, Shivakoti R, Singh GM, Sleet DA, Smith E, Smith KR, Stapelberg NJ, Steenland K, Stöckl H, Stovner LJ, Straif K, Straney L, Thurston GD, Tran JH, Van Dingenen R, van Donkelaar A, Veerman JL, Vijayakumar L, Weintraub R, Weissman MM, White RA, Whiteford H, Wiersma ST, Wilkinson JD, Williams HC, Williams W, Wilson N, Woolf AD, Yip P, Zielinski JM, Lopez AD, Murray CJ, Ezzati M, AlMazroa MA, Memish ZA. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380(9859):2224–60. doi: 10.1016/S0140-6736(12)61766-8.
    1. Office for National Statistics. 2009. Mortality statistics: Deaths registered in England and Wales (Series DR), 2008 .
    1. Noar SM. A 10-year retrospective of research in health mass media campaigns: where do we go from here? J Health Commun. 2006;11(1):21–42. doi: 10.1080/10810730500461059.
    1. Davies CA, Spence JC, Vandelanotte C, Caperchione CM, Mummery WK. Meta-analysis of Internet-delivered interventions to increase physical activity levels. Int J Behav Nutr Phys Act. 2012;9(1):52. doi: 10.1186/1479-5868-9-52.
    1. Bennett GG, Glasgow RE. The delivery of public health interventions via the Internet: actualizing their potential. Annu Rev Public Health. 2009;30:273–92. doi: 10.1146/annurev.publhealth.031308.100235.
    1. Habeshian V. Marketing Profs. 2013. Social takes up 27% of time spent online .
    1. comScore Data Mine. 2013. A digital month in Germany: what are consumers doing online?
    1. Constine J. Techcrunch. 2013. Facebook’s Q2: Monthly users up 21% YOY to 1.15B, dailies up 27% to 699M, mobile monthlies up 51% to 819M
    1. De Bruyn A, Lilien GL. A multi-stage model of word-of-mouth influence through viral marketing. Int J Market Res. 2008;25(3):151–63. doi: 10.1016/j.ijresmar.2008.03.004.
    1. Thackeray R, Neiger BL, Hanson CL, McKenzie JF. Enhancing promotional strategies within social marketing programs: use of Web 2.0 social media. Health Promot Pract. 2008;9(4):338–43. doi: 10.1177/1524839908325335.
    1. Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097. doi: 10.1371/journal.pmed.1000097.
    1. Sampson M, McGowan J, Cogo E, Grimshaw J, Moher D, Lefebvre C. An evidence-based practice guideline for the peer review of electronic search strategies. J Clin Epidemiol. 2009;62(9):944–52. doi: 10.1016/j.jclinepi.2008.10.012.
    1. Higgins JPT, Green S. The Cochrane Collaboration. 2011. Cochrane handbook for systematic reviews of interventions version 5.1.0 .
    1. Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JP, Clarke M, Devereaux PJ, Kleijnen J, Moher D. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ. 2009;339:b2700.
    1. Schulz KF, Altman DG, Moher D, CONSORT Group CONSORT 2010 Statement: updated guidelines for reporting parallel group randomized trials. Open Med. 2010;4(1):e60–8.
    1. Oxford Centre for Evidence-Based Medicine. 2013. The Oxford levels of evidence 2 .
    1. Lipsey MW, Wilson D. Practical meta-analysis. Thousand Oaks, California: SAGE Publications; 2001.
    1. Wilson DB. Practical Meta-Analysis Effect Size Calculator. -. [2014-01-23]. .
    1. Thalheimer W, Cook S. How to calculate effect sizes from published research: a simplified methodology. 2002. .
    1. Brindal E, Freyne J, Saunders I, Berkovsky S, Smith G, Noakes M. Features predicting weight loss in overweight or obese participants in a web-based intervention: randomized trial. J Med Internet Res. 2012;14(6):e173. doi: 10.2196/jmir.2156.
    1. Foster D, Linehan C, Kirman B, Lawson S, James G. Motivating physical activity at work: using persuasive social media for competitive step counting. 14th International Academic MindTrek Conference: Envisioning Future Media Environments, MindTrek; Oct 6-8, 2010; Tampere. 2010. pp. 111–6.
    1. Freyne J, Berkovsky S, Kimani S, Baghaei N, Brindal E. Improving health information access through social networking. 23rd IEEE International Symposium on Computer-Based Medical Systems, CBMS; Oct 12-15, 2010; Perth. 2010. pp. 334–9.
    1. Ma X, Chen G, Xiao J. Analysis of an online health social network. 1st ACM International Health Informatics Symposium, IHI'10; Nov 11-12, 2010; Arlington. 2010. pp. 297–306.
    1. Sugano M, Yamazaki C. Behavioral analysis of SNS users with regard to diet. IADIS International Conferences - Web Based Communities and Social Media 2011, Social Media 2011, Internet Applications and Research 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS; July 20-26, 2011; Rome. 2011. pp. 167–70.
    1. Valle CG, Tate DF, Mayer DK, Allicock M, Cai J. A randomized trial of a Facebook-based physical activity intervention for young adult cancer survivors. J Cancer Surviv. 2013;7(3):355–68. doi: 10.1007/s11764-013-0279-5.
    1. Turner-McGrievy G, Tate D. Tweets, apps, and pods: results of the 6-month Mobile Pounds Off Digitally (Mobile POD) randomized weight-loss intervention among adults. J Med Internet Res. 2011;13(4):e120. doi: 10.2196/jmir.1841.
    1. Napolitano MA, Hayes S, Bennett GG, Ives AK, Foster GD. Using Facebook and text messaging to deliver a weight loss program to college students. Obesity (Silver Spring) 2013;21(1):25–31. doi: 10.1002/oby.20232.
    1. Kuwata S, Taniguchi S, Kato A, Inoue K, Yamamoto N, Ohkura T, Teramoto K, Shigemasa C, Kondoh H. Metaboli-Net: online groupware system providing counseling guidance for patients with metabolic syndrome. Stud Health Technol Inform. 2010;156:65–70.
    1. Cavallo DN, Tate DF, Ries AV, Brown JD, DeVellis RF, Ammerman AS. A social media-based physical activity intervention: a randomized controlled trial. Am J Prev Med. 2012;43(5):527–32. doi: 10.1016/j.amepre.2012.07.019.
    1. Kaushal N. Facebook to roll-out country wise metrics of monthly active users & daily active users! PageTraffic Buzz. 2013. [2013-09-05].
    1. Ellison NB, Steinfield C, Lampe C. The benefits of Facebook “friends": social capital and college students’ use of online social network sites. J Comput-Mediat Comm. 2007;12(4):1143–68. doi: 10.1111/j.1083-6101.2007.00367.x.
    1. Cheung CM, Chiu P, Lee MK. Online social networks: why do students use Facebook? Comput Hum Behav. 2011;27(4):1337–43. doi: 10.1016/j.chb.2010.07.028.
    1. Jepson RG, Harris FM, Platt S, Tannahill C. The effectiveness of interventions to change six health behaviours: a review of reviews. BMC Public Health. 2010;10(1):538. doi: 10.1186/1471-2458-10-538.
    1. Deterding S, Sicart M, Nacke L, O'Hara K, Dixon D. Gamification. Using game-design elements in non-gaming contexts. CHI '11 Extended Abstracts on Human Factors in Computing Systems; May 7-12, 2011; Vancouver. 2011. pp. 2425–8.
    1. Fenner Y, Garland SM, Moore EE, Jayasinghe Y, Fletcher A, Tabrizi SN, Gunasekaran B, Wark JD. Web-based recruiting for health research using a social networking site: an exploratory study. J Med Internet Res. 2012;14(1):e20. doi: 10.2196/jmir.1978.
    1. Wakefield MA, Loken B, Hornik RC. Use of mass media campaigns to change health behaviour. Lancet. 2010;376(9748):1261–71. doi: 10.1016/S0140-6736(10)60809-4.

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